News
2019 - Exploring different imaging technologies for prostate cancer
Dr. Baowei Fei’s research on prostate cancer imaging has been featured by SciTech Europa Quarterly that provides opportunities to leading figures from across Europe to discuss current and future projects, policy change and future priorities within research and development, as well as being a platform for others to voice their opinions and showcase their results to Europe’s research community. For more information, read the PDF file of the article or visit the following websites: https://www.scitecheuropa.eu/exploring-different-imaging-technologies-for-prostate-cancer/98656 https://www.scitecheuropa.eu/scitech-europa-quarterly-issue-33/98760/ [Learn more]
Dr. Baowei Fei’s research on prostate cancer imaging has been featured by SciTech Europa Quarterly that provides opportunities to leading figures from across Europe to discuss current and future projects, policy change and future priorities within research and development, as well as being a platform for others to voice their opinions and showcase their results to Europe’s research community. For more information, read the PDF file of the article or visit the following websites: https://www.scitecheuropa.eu/exploring-different-imaging-technologies-for-prostate-cancer/98656 https://www.scitecheuropa.eu/scitech-europa-quarterly-issue-33/98760/ [Learn more]
2019 - Researchers at UT Dallas advance fight to end cancer
Community Impact Newspaper reported the cancer research work that were conducted at the University of Texas at Dallas. Community Impact Newspaper is vested in the communities and has dedicated reporters in each community who attend city council and school board meetings. Community Impact Newspaper distributes hyperlocal news and information to millions of local residents and business owners each day online and monthly by mail. For more information, read the article from the following website: https://communityimpact.com/guides/dallas-fort-worth/richardson/news/education/2019/10/24/researchers-at-ut-dallas-advance-fight-to-end-cancer/ [Learn more]
Community Impact Newspaper reported the cancer research work that were conducted at the University of Texas at Dallas. Community Impact Newspaper is vested in the communities and has dedicated reporters in each community who attend city council and school board meetings. Community Impact Newspaper distributes hyperlocal news and information to millions of local residents and business owners each day online and monthly by mail. For more information, read the article from the following website: https://communityimpact.com/guides/dallas-fort-worth/richardson/news/education/2019/10/24/researchers-at-ut-dallas-advance-fight-to-end-cancer/ [Learn more]
2019 - Novel Imaging Technique and AI Create Smart Microscope for Cancer Surgery
Dr. Baowei Fei and his group have recently used a unique imaging technology and artificial intelligence (AI) to predict the presence of cancer cells in tissue samples. This hyperspectral imaging technique is effective in satellite imagery and orbiting telescopes. It could be used to quickly identify cancer cells in the operating room as well. Analyzing 293 tissue samples from 102 head and neck cancer surgery patients, Fei and colleagues found that hyperspectral imaging and AI could be used to predict cancer cell presence with 80-90% accuracy. Dr. Fei recently received a $1.6 million grant from the Cancer Prevention & Research Institute of Texas (CPRIT) to continue improving this smart surgical microscope. Once this approach is fully developed, it would need to be tested in clinical studies before being used in the live healthcare environment. For more information, visit the following website: https://www.docwirenews.com/docwire-pick/novel-imaging-technique-and-ai-create-smart-microscope-for-cancer-surgery/ [Learn more]
Dr. Baowei Fei and his group have recently used a unique imaging technology and artificial intelligence (AI) to predict the presence of cancer cells in tissue samples. This hyperspectral imaging technique is effective in satellite imagery and orbiting telescopes. It could be used to quickly identify cancer cells in the operating room as well. Analyzing 293 tissue samples from 102 head and neck cancer surgery patients, Fei and colleagues found that hyperspectral imaging and AI could be used to predict cancer cell presence with 80-90% accuracy. Dr. Fei recently received a $1.6 million grant from the Cancer Prevention & Research Institute of Texas (CPRIT) to continue improving this smart surgical microscope. Once this approach is fully developed, it would need to be tested in clinical studies before being used in the live healthcare environment. For more information, visit the following website: https://www.docwirenews.com/docwire-pick/novel-imaging-technique-and-ai-create-smart-microscope-for-cancer-surgery/ [Learn more]
2019 - Building a brighter way for capturing cancer during surgery
The research work by Dr. Baowei Fei’s Lab has been featured by AAAS and EurekAlert!. In a study published in the Sept. 14 edition of the journal Cancers, Dr. Fei and colleagues showed that hyperspectral imaging and artificial intelligence could predict the presence of cancer cells with 80% to 90% accuracy in 293 tissue specimens from 102 head and neck cancer surgery patients. Dr. Fei recently received a $1.6 million grant from the Cancer Prevention & Research Institute of Texas (CPRIT) to further develop the technology, called a smart surgical microscope. For more information, visit the following website: https://www.eurekalert.org/pub_releases/2019-09/uota-bab093019.php [Learn more]
The research work by Dr. Baowei Fei’s Lab has been featured by AAAS and EurekAlert!. In a study published in the Sept. 14 edition of the journal Cancers, Dr. Fei and colleagues showed that hyperspectral imaging and artificial intelligence could predict the presence of cancer cells with 80% to 90% accuracy in 293 tissue specimens from 102 head and neck cancer surgery patients. Dr. Fei recently received a $1.6 million grant from the Cancer Prevention & Research Institute of Texas (CPRIT) to further develop the technology, called a smart surgical microscope. For more information, visit the following website: https://www.eurekalert.org/pub_releases/2019-09/uota-bab093019.php [Learn more]
2019 - New CPRIT Grant to Develop Smart Surgical Microscope and Artificial Intelligence
Dr. Baowei Fei, the Cecil H. and Ida Green Chair in Systems Biology Science at UT Dallas, is developing a smart surgical microscope that uses hyperspectral imaging and artificial intelligence to detect cancer cells during surgery. He recently received a $1.6 million grant from the Cancer Prevention & Research Institute of Texas (CPRIT) to further develop the technology. Hyperspectral imaging, originally used in satellite imagery, orbiting telescopes and other applications, goes beyond what the human eye can see as cells are examined under ultraviolet and near-infrared lights at micrometer resolution. By analyzing how cells reflect and absorb light across the electromagnetic spectrum, experts can get a spectral image of cells that is as unique as a fingerprint. For more information, visit the following website: https://www.utdallas.edu/news/research/cancer-smart-surgical-microscope-fei-2019/ [Learn more]
Dr. Baowei Fei, the Cecil H. and Ida Green Chair in Systems Biology Science at UT Dallas, is developing a smart surgical microscope that uses hyperspectral imaging and artificial intelligence to detect cancer cells during surgery. He recently received a $1.6 million grant from the Cancer Prevention & Research Institute of Texas (CPRIT) to further develop the technology. Hyperspectral imaging, originally used in satellite imagery, orbiting telescopes and other applications, goes beyond what the human eye can see as cells are examined under ultraviolet and near-infrared lights at micrometer resolution. By analyzing how cells reflect and absorb light across the electromagnetic spectrum, experts can get a spectral image of cells that is as unique as a fingerprint. For more information, visit the following website: https://www.utdallas.edu/news/research/cancer-smart-surgical-microscope-fei-2019/ [Learn more]
2019 - New NIH Grant to Support Research on Deep Learning for CT Image Standardization
Lung cancer is the leading cause of cancer death and one of the most common cancers among both men and women in the United States. Recent advances in high-resolution imaging set the stage for radiomics to become an active emerging field in cancer research. However, the promise of radiomics is limited by a lack of image standardization tools, because computed tomography (CT) images are often acquired using scanners from different vendors with customized acquisition parameters, posing a fundamental challenge to radiomic studies across sites. To overcome this challenge, especially for large-scale, multi-site radiomic studies, advanced algorithms are required to integrate, standardize, and normalize CT images from multiple sources. We propose to develop STAN-CT, a deep learning software package that can automatically standardize and normalize a large volume of diagnostic images to facilitate cross-site large-scale image feature extraction for lung cancer characterization and stratification. STAN-CT will enable a wide range of radiomic researches to identify diagnostic image features that strongly associated with lung cancer prognosis. [Learn more]
Lung cancer is the leading cause of cancer death and one of the most common cancers among both men and women in the United States. Recent advances in high-resolution imaging set the stage for radiomics to become an active emerging field in cancer research. However, the promise of radiomics is limited by a lack of image standardization tools, because computed tomography (CT) images are often acquired using scanners from different vendors with customized acquisition parameters, posing a fundamental challenge to radiomic studies across sites. To overcome this challenge, especially for large-scale, multi-site radiomic studies, advanced algorithms are required to integrate, standardize, and normalize CT images from multiple sources. We propose to develop STAN-CT, a deep learning software package that can automatically standardize and normalize a large volume of diagnostic images to facilitate cross-site large-scale image feature extraction for lung cancer characterization and stratification. STAN-CT will enable a wide range of radiomic researches to identify diagnostic image features that strongly associated with lung cancer prognosis. [Learn more]
2019 - A New Technique for Targeted Prostate Cancer Biopsies
Dr. Baowei Fei’s research on prostate cancer biopsy has been featured by Scientia Global that is a series of outreach research publications. Scientia Global connects people: scientists and educators, policy-makers and researchers, and the public and private sectors, and helps researchers communicate their findings beyond their specialty and into the wider world. Scientia offers the research community significant visibility and accessibility to those both inside and outside the community to take an interest in science and research. Dr. Fei is pioneering a technique that merges positron emission tomography (PET) with ultrasound imaging to detect prostate cancer more accurately than before. For more information, read the PDF file of the article or visit the following websites: https://www.scientia.global/dr-baowei-fei-a-new-technique-for-targeted-prostate-cancer-biopsies/ [Learn more]
Dr. Baowei Fei’s research on prostate cancer biopsy has been featured by Scientia Global that is a series of outreach research publications. Scientia Global connects people: scientists and educators, policy-makers and researchers, and the public and private sectors, and helps researchers communicate their findings beyond their specialty and into the wider world. Scientia offers the research community significant visibility and accessibility to those both inside and outside the community to take an interest in science and research. Dr. Fei is pioneering a technique that merges positron emission tomography (PET) with ultrasound imaging to detect prostate cancer more accurately than before. For more information, read the PDF file of the article or visit the following websites: https://www.scientia.global/dr-baowei-fei-a-new-technique-for-targeted-prostate-cancer-biopsies/ [Learn more]
2019 - Past Bonds, Future Enrichment Come Together at Investiture Ceremony
Considered the highest academic honor a university can bestow, chair and professorship endowments provide senior-level faculty with funds to advance their scholarly activities and support research at the University of Texas at Dallas. Investitures are among the oldest traditions in academia, dating back more than 500 years. During the ceremony, honorees and ceremonial participants don full academic regalia. The endowed chairs and professorships are made possible by philanthropic donations, with several established by or honoring the University’s founders and early leaders. https://www.utdallas.edu/news/faculty/investiture-coverage-2019/ [Learn more]
Considered the highest academic honor a university can bestow, chair and professorship endowments provide senior-level faculty with funds to advance their scholarly activities and support research at the University of Texas at Dallas. Investitures are among the oldest traditions in academia, dating back more than 500 years. During the ceremony, honorees and ceremonial participants don full academic regalia. The endowed chairs and professorships are made possible by philanthropic donations, with several established by or honoring the University’s founders and early leaders. https://www.utdallas.edu/news/faculty/investiture-coverage-2019/ [Learn more]
2019 - Dr. Baowei Fei Honored at the University Investiture Ceremony
Dr. Baowei Fei is honored at the University Investiture Ceremony. President Richard C. Benson and Dr. Poras Balsara, interim dean of the Erik Jonsson School of Engineering and Computer Science, presented a medallion to Dr. Baowei Fei, Cecil H. and Ida M. Green Chair in Systems Biology Science. Twelve faculty members who were formally honored hold professorships and chairs in the Office of Graduate Education, School of Behavioral and Brain Sciences, Erik Jonsson School of Engineering and Computer Science, Naveen Jindal School of Management and the School of Natural Sciences and Mathematics. Dr. Baowei Fei, an imaging scientist and cancer scholar whose work has transformed medical imaging and intervention for cancer care and who teaches in the Department of Bioengineering in the Jonsson School, is among those recognized at the ceremony. https://www.utdallas.edu/news/faculty/investiture-ceremony-to-honor-faculty-donors/ [Learn more]
Dr. Baowei Fei is honored at the University Investiture Ceremony. President Richard C. Benson and Dr. Poras Balsara, interim dean of the Erik Jonsson School of Engineering and Computer Science, presented a medallion to Dr. Baowei Fei, Cecil H. and Ida M. Green Chair in Systems Biology Science. Twelve faculty members who were formally honored hold professorships and chairs in the Office of Graduate Education, School of Behavioral and Brain Sciences, Erik Jonsson School of Engineering and Computer Science, Naveen Jindal School of Management and the School of Natural Sciences and Mathematics. Dr. Baowei Fei, an imaging scientist and cancer scholar whose work has transformed medical imaging and intervention for cancer care and who teaches in the Department of Bioengineering in the Jonsson School, is among those recognized at the ceremony. https://www.utdallas.edu/news/faculty/investiture-ceremony-to-honor-faculty-donors/ [Learn more]
2019 - Bioengineer Recognized Among Top in His Field with AIMBE Honor
Dr. Baowei Fei, a distinguished bioengineer at The University of Texas at Dallas, has been elected to the College of Fellows of the American Institute for Medical and Biological Engineering (AIMBE), an honor that represents the top 2 percent of individuals in medical and biological engineering. The College of Fellows comprises more than 2,000 outstanding medical and biological engineers in academia, industry and government, including engineering and medical school chairs, research directors, professors, innovators and successful entrepreneurs. https://www.utdallas.edu/news/faculty/bioengineer-elected-aimbe-fellow-2019/ [Learn more]
Dr. Baowei Fei, a distinguished bioengineer at The University of Texas at Dallas, has been elected to the College of Fellows of the American Institute for Medical and Biological Engineering (AIMBE), an honor that represents the top 2 percent of individuals in medical and biological engineering. The College of Fellows comprises more than 2,000 outstanding medical and biological engineers in academia, industry and government, including engineering and medical school chairs, research directors, professors, innovators and successful entrepreneurs. https://www.utdallas.edu/news/faculty/bioengineer-elected-aimbe-fellow-2019/ [Learn more]
2019 - NBC News Featured Research Work on Molecular Imaging and Targeted Biopsy
NBC News featured the research work by Dr. Baowei Fei and his team. The technology that was developed in his research lab is called molecular imaging directed, 3D ultrasound-guided biopsy, which improved upon 2D systems by allowing for earlier detection of potentially cancerous cells in the prostate. The new technology has been evaluated by an early phase clinical trial and the clinical finds were published Journal of Urology (Fei et al, Feasibility and Initial Results: Fluciclovine Positron Emission Tomography/Ultrasound Fusion Targeted Biopsy of Recurrent Prostate Cancer. Journal of Urology. 2019;202(2):413-421). For more information, read the PDF file of the clinical paper or visit the following website for the NBC news. https://www.nbcdfw.com/news/local/researcher-finds-cancer-earlier-with-new-imaging-technology/9491/ [Learn more]
NBC News featured the research work by Dr. Baowei Fei and his team. The technology that was developed in his research lab is called molecular imaging directed, 3D ultrasound-guided biopsy, which improved upon 2D systems by allowing for earlier detection of potentially cancerous cells in the prostate. The new technology has been evaluated by an early phase clinical trial and the clinical finds were published Journal of Urology (Fei et al, Feasibility and Initial Results: Fluciclovine Positron Emission Tomography/Ultrasound Fusion Targeted Biopsy of Recurrent Prostate Cancer. Journal of Urology. 2019;202(2):413-421). For more information, read the PDF file of the clinical paper or visit the following website for the NBC news. https://www.nbcdfw.com/news/local/researcher-finds-cancer-earlier-with-new-imaging-technology/9491/ [Learn more]
2019 - Dr. Baowei Fei Named Fellow of International Society for Optics and Photonics (SPIE)
Dr. Baowei Fei was recently named a new Fellow of the International Society for Optics and Photonics (SPIE) and will be honored at the Plenary Session of the International Conference of SPIE Medical Imaging in San Diego, CA on February 18, 2019. The SPIE was founded in 1955 to advance light-based technologies. Serving more than 264,000 constituents from approximately 166 countries, the not-for-profit society advances emerging technologies through interdisciplinary information exchange, continuing education, publications, patent precedent, and career and professional growth. SPIE annually organizes and sponsors approximately 25 major technical forums, exhibitions, and education programs in North America, Europe, Asia, and the South Pacific. https://be.utdallas.edu//about/news/professor-elected-as-fellow-of-the-international-society-for-optics-and-photonics/ [Learn more]
Dr. Baowei Fei was recently named a new Fellow of the International Society for Optics and Photonics (SPIE) and will be honored at the Plenary Session of the International Conference of SPIE Medical Imaging in San Diego, CA on February 18, 2019. The SPIE was founded in 1955 to advance light-based technologies. Serving more than 264,000 constituents from approximately 166 countries, the not-for-profit society advances emerging technologies through interdisciplinary information exchange, continuing education, publications, patent precedent, and career and professional growth. SPIE annually organizes and sponsors approximately 25 major technical forums, exhibitions, and education programs in North America, Europe, Asia, and the South Pacific. https://be.utdallas.edu//about/news/professor-elected-as-fellow-of-the-international-society-for-optics-and-photonics/ [Learn more]
2019 - Robert F. Wagner All Conferences Best Student Paper Award
Himar Fabelo, a PhD student from Dr. Baowei Fei’s Lab, received the Robert F. Wagner All Conference Best Student Paper Award – Runner-Up at the International Conferences of SPIE Medical Imaging in San Diego, California on February 18, 2018. The title of his paper is “Surgical aid visualization system for glioblastoma tumor identification based on deep learning and invivo hyperspectral images of human patients.” The Robert F. Wagner All Conference Best Student Paper Award (established 2014) is an acknowledgement of his many important contributions to the Medical Imaging meeting and his many important advances in the field of medical imaging and is co-sponsored The Medical Imaging Perception Society and SPIE. A first-place winner and runner-up were recognized with a cash prize ($1,000 and $500 respectively) and a certificate during the Plenary Session at the conference. [Learn more]
Himar Fabelo, a PhD student from Dr. Baowei Fei’s Lab, received the Robert F. Wagner All Conference Best Student Paper Award – Runner-Up at the International Conferences of SPIE Medical Imaging in San Diego, California on February 18, 2018. The title of his paper is “Surgical aid visualization system for glioblastoma tumor identification based on deep learning and invivo hyperspectral images of human patients.” The Robert F. Wagner All Conference Best Student Paper Award (established 2014) is an acknowledgement of his many important contributions to the Medical Imaging meeting and his many important advances in the field of medical imaging and is co-sponsored The Medical Imaging Perception Society and SPIE. A first-place winner and runner-up were recognized with a cash prize ($1,000 and $500 respectively) and a certificate during the Plenary Session at the conference. [Learn more]
2019 - Undergraduate Student, Amol Mavuduru, won the 2019 Jonsson School Undergraduate Experience Research Award at the University of Texas at Dallas
The Undergraduate Research Awards at the Erik Jonsson School of Engineering and Computer Science offer engineering majors financial support to work with a top Jonsson School faculty member on relevant research projects. The $500 awards give students the opportunity to build practical experience that opens doors for graduate school, internships, and careers. Amol Mavuduru, an undergraduate student from Dr. Baowei Fei’s lab, won the 2019 Jonsson School Undergraduate Experience Research Award. [Learn more]
The Undergraduate Research Awards at the Erik Jonsson School of Engineering and Computer Science offer engineering majors financial support to work with a top Jonsson School faculty member on relevant research projects. The $500 awards give students the opportunity to build practical experience that opens doors for graduate school, internships, and careers. Amol Mavuduru, an undergraduate student from Dr. Baowei Fei’s lab, won the 2019 Jonsson School Undergraduate Experience Research Award. [Learn more]
2019 - Undergraduate Student, James Huang, won the 2019 Undergraduate Research Scholar Award (URSA) from the Office of Undergraduate Education at the University of Texas at Dallas
The Undergraduate Research Scholar Awards are a one-time competitive award made by the Office of Undergraduate Education at the University of Texas at Dallas, designed to reward the contributions and facilitate the professional development of undergraduate researchers at the University of Texas at Dallas. Students selected to receive an Undergraduate Research Scholar Award receive $500 and the certificate, awarded upon participation in the Undergraduate Research Scholar Award poster competition held in mid-April. James Huang, an undergraduate student from Dr. Baowei Fei’s lab, won the 2019 Undergraduate Research Scholar Award. [Learn more]
The Undergraduate Research Scholar Awards are a one-time competitive award made by the Office of Undergraduate Education at the University of Texas at Dallas, designed to reward the contributions and facilitate the professional development of undergraduate researchers at the University of Texas at Dallas. Students selected to receive an Undergraduate Research Scholar Award receive $500 and the certificate, awarded upon participation in the Undergraduate Research Scholar Award poster competition held in mid-April. James Huang, an undergraduate student from Dr. Baowei Fei’s lab, won the 2019 Undergraduate Research Scholar Award. [Learn more]
2019 - Robert F. Wagner All Conferences Best Student Paper Award
Himar Fabelo, a PhD student from Dr. Baowei Fei’s Lab, received the Robert F. Wagner All Conference Best Student Paper Award – Runner-Up at the International Conferences of SPIE Medical Imaging in San Diego, California on February 18, 2019. The title of his paper is “Surgical aid visualization system for glioblastoma tumor identification based on deep learning and in vivo hyperspectral images of human patients.” The Robert F. Wagner All Conference Best Student Paper Award (established 2014) is an acknowledgement of his many important contributions to the Medical Imaging meeting and his many important advances in the field of medical imaging and is co-sponsored The Medical Imaging Perception Society and SPIE. A first-place winner and runner-up were recognized with a cash prize ($1,000 and $500 respectively) and a certificate during the Plenary Session at the conference. [Learn more]
Himar Fabelo, a PhD student from Dr. Baowei Fei’s Lab, received the Robert F. Wagner All Conference Best Student Paper Award – Runner-Up at the International Conferences of SPIE Medical Imaging in San Diego, California on February 18, 2019. The title of his paper is “Surgical aid visualization system for glioblastoma tumor identification based on deep learning and in vivo hyperspectral images of human patients.” The Robert F. Wagner All Conference Best Student Paper Award (established 2014) is an acknowledgement of his many important contributions to the Medical Imaging meeting and his many important advances in the field of medical imaging and is co-sponsored The Medical Imaging Perception Society and SPIE. A first-place winner and runner-up were recognized with a cash prize ($1,000 and $500 respectively) and a certificate during the Plenary Session at the conference. [Learn more]
2018 - Dr. Baowei Fei serves as the Chair for the NIH Study Section: ZCA1 RPRB-N (J2) Integrating Biospecimens into Clinical Assay Development (U01)
This Funding Opportunity Announcement (FOA) will support extramural research to investigate and mitigate challenges facing clinical assay development due to biopsy biospecimen preanalytical variability. The program will tie in with current efforts to optimize clinical biomarker assays utilized in NCI-sponsored clinical trials. Results from this research program will improve the understanding of how biopsy collection, processing, and storage procedures may affect all aspects of analytical performance for current and emerging clinical biomarkers, as well as expedite clinical biomarker assay development through the evidence-based standardization of biopsy handling practices. Critical information gained through these research awards may increase the reliability of clinical biomarker assays, reduce time requirements for assay development, and decrease assay failure during late-stage testing. [Learn more]
This Funding Opportunity Announcement (FOA) will support extramural research to investigate and mitigate challenges facing clinical assay development due to biopsy biospecimen preanalytical variability. The program will tie in with current efforts to optimize clinical biomarker assays utilized in NCI-sponsored clinical trials. Results from this research program will improve the understanding of how biopsy collection, processing, and storage procedures may affect all aspects of analytical performance for current and emerging clinical biomarkers, as well as expedite clinical biomarker assay development through the evidence-based standardization of biopsy handling practices. Critical information gained through these research awards may increase the reliability of clinical biomarker assays, reduce time requirements for assay development, and decrease assay failure during late-stage testing. [Learn more]
2018 - Dr. Baowei Fei serves as a Panel Member of the NIH Study Section: Biomedical Imaging Technology (BMIT-B)
The Biomedical Imaging Technology Study Sections both review applications involving basic, applied, and pre-clinical aspects of the design and development of medical imaging system technologies, their components, software, and mathematical methods for studies at the cellular, organ, small or large animal, and human scale. [Learn more]
The Biomedical Imaging Technology Study Sections both review applications involving basic, applied, and pre-clinical aspects of the design and development of medical imaging system technologies, their components, software, and mathematical methods for studies at the cellular, organ, small or large animal, and human scale. [Learn more]
2018 - Dr. Baowei Fei was appointed as Cecil H. and Ida Green Chair in Systems Biology Science by the University of Texas at Dallas
Provost Musselman of the University of Texas at Dallas appointed Dr. Baowei Fei to the endowed faculty position Cecil H. and Ida Green Chair in Systems Biology Science #3, one of the honorific appointment awarded by the University to its most distinguished faculty members. [Learn more]
Provost Musselman of the University of Texas at Dallas appointed Dr. Baowei Fei to the endowed faculty position Cecil H. and Ida Green Chair in Systems Biology Science #3, one of the honorific appointment awarded by the University to its most distinguished faculty members. [Learn more]
2018 - Noted Cancer Scholar Joins Jonsson School’s Bioengineering Team
Dr. Baowei Fei, a professor of bioengineering, was previously an associate professor at Emory University School of Medicine and the Georgia Institute of Technology. “Dr. Fei is a world-class researcher in the area of image-guided intervention,” said Dr. Robert Rennaker, Texas Instruments Distinguished Chair in Bioengineering and head of the Department of Bioengineering. “Our ability to recruit faculty members of his caliber is what will propel UT Dallas to national prominence as we strengthen our partnership with UT Southwestern Medical Center. Dr. Fei has received numerous honors and awards, including the Distinguished Investigator Award from the Academy for Radiology & Biomedical Imaging Research and the Young Investigator Award from the Society of Nuclear Medicine and Molecular Imaging. In 2009 he was recognized as a Distinguished Cancer Scholar by the Georgia Cancer Coalition. He also served as the Conference Chair for the SPIE Medical Imaging: Image-guided Interventions, Robotic Interventions, and Modeling Conference 2017-2020. https://engineering.utdallas.edu//news/archive/2018-summer/world-class-imaging-scientist-cancer-scholar-joins-university/ [Learn more]
Dr. Baowei Fei, a professor of bioengineering, was previously an associate professor at Emory University School of Medicine and the Georgia Institute of Technology. “Dr. Fei is a world-class researcher in the area of image-guided intervention,” said Dr. Robert Rennaker, Texas Instruments Distinguished Chair in Bioengineering and head of the Department of Bioengineering. “Our ability to recruit faculty members of his caliber is what will propel UT Dallas to national prominence as we strengthen our partnership with UT Southwestern Medical Center. Dr. Fei has received numerous honors and awards, including the Distinguished Investigator Award from the Academy for Radiology & Biomedical Imaging Research and the Young Investigator Award from the Society of Nuclear Medicine and Molecular Imaging. In 2009 he was recognized as a Distinguished Cancer Scholar by the Georgia Cancer Coalition. He also served as the Conference Chair for the SPIE Medical Imaging: Image-guided Interventions, Robotic Interventions, and Modeling Conference 2017-2020. https://engineering.utdallas.edu//news/archive/2018-summer/world-class-imaging-scientist-cancer-scholar-joins-university/ [Learn more]
2018 - World-Class Imaging Scientist, Cancer Scholar Joins University
Dr. Baowei Fei, an imaging scientist and cancer scholar whose work has transformed medical imaging and intervention for cancer care, recently joined the UT Dallas Department of Bioengineering. Dr. Fei was inspired by a speech by University President Richard C. Benson that he paraphrases: “‘We are still giving shape to this superb University, defining purpose and creating tradition that will last for 100 years and more. Put simply: you are founders,’” Dr. Fei’s group developed a technology called the molecular imaging directed, 3D ultrasound-guided biopsy system, which improves upon 2D systems by allowing for earlier detection of potentially cancerous cells in the prostate. Dr. Fei led the first clinical trial of positron emission tomography (PET) combined with ultrasound fusion targeted biopsy of the prostate. His research group also is investigating a technology called hyperspectral imaging for its potential use in biological and medical applications, such as real-time detection of cancer cells during surgery for complete removal of the tumor. The technology provides information about healthy and diseased tissues based on how they interact with various wavelengths of light. https://engineering.utdallas.edu//news/archive/2018-summer/world-class-imaging-scientist-cancer-scholar-joins-university/ [Learn more]
Dr. Baowei Fei, an imaging scientist and cancer scholar whose work has transformed medical imaging and intervention for cancer care, recently joined the UT Dallas Department of Bioengineering. Dr. Fei was inspired by a speech by University President Richard C. Benson that he paraphrases: “‘We are still giving shape to this superb University, defining purpose and creating tradition that will last for 100 years and more. Put simply: you are founders,’” Dr. Fei’s group developed a technology called the molecular imaging directed, 3D ultrasound-guided biopsy system, which improves upon 2D systems by allowing for earlier detection of potentially cancerous cells in the prostate. Dr. Fei led the first clinical trial of positron emission tomography (PET) combined with ultrasound fusion targeted biopsy of the prostate. His research group also is investigating a technology called hyperspectral imaging for its potential use in biological and medical applications, such as real-time detection of cancer cells during surgery for complete removal of the tumor. The technology provides information about healthy and diseased tissues based on how they interact with various wavelengths of light. https://engineering.utdallas.edu//news/archive/2018-summer/world-class-imaging-scientist-cancer-scholar-joins-university/ [Learn more]
2018 - Dr. Fei received a new NIH R01 grant on image-guided intravascular robotic system for mitral valve repair and implants.
Mitral regurgitation (MR) is one of the most common valve lesions, which affects 9 million Americans, and is known to increase morbidity and mortality. MR occurs due to leakage of blood through the mitral valve and induces volume overload on the left ventricle, elevates diastolic wall stress and causes rapid left ventricular dilatation, ultimately leading to congestive heart failure within 5 years and death. Timely and effective repair of MR is of utmost importance to halt the progression of heart failure, but current options are limited. Open- heart surgery is the current standard of care and has a relatively high risk of post-operative mortality. Transcatheter mitral valve repair, is a new class of technologies in which MR repair is performed on a beating heart using a catheter that is guided to the mitral valve to deploy reparative devices. However, the route to the mitral valve is a challenging path for existing catheters to follow. The complexity associated with their implantation in a beating heart, often leads to failed procedures and conversion to open heart surgery. We propose to develop a novel intravascular steerable robot that is guided to the mitral valve by multimodality imaging and deploys a novel, low profile device that can effectively repair MR of all forms. This highly innovative and interdisciplinary project combines expertise in surgical robotics, imaging and mitral repair devices. We envision that the intravascular steerable robot and implant, guided by multimodality imaging will significantly simplify Transcatheter mitral valve repair, increasing the procedural accuracy and control, and reducing failure rates. [Learn more]
Mitral regurgitation (MR) is one of the most common valve lesions, which affects 9 million Americans, and is known to increase morbidity and mortality. MR occurs due to leakage of blood through the mitral valve and induces volume overload on the left ventricle, elevates diastolic wall stress and causes rapid left ventricular dilatation, ultimately leading to congestive heart failure within 5 years and death. Timely and effective repair of MR is of utmost importance to halt the progression of heart failure, but current options are limited. Open- heart surgery is the current standard of care and has a relatively high risk of post-operative mortality. Transcatheter mitral valve repair, is a new class of technologies in which MR repair is performed on a beating heart using a catheter that is guided to the mitral valve to deploy reparative devices. However, the route to the mitral valve is a challenging path for existing catheters to follow. The complexity associated with their implantation in a beating heart, often leads to failed procedures and conversion to open heart surgery. We propose to develop a novel intravascular steerable robot that is guided to the mitral valve by multimodality imaging and deploys a novel, low profile device that can effectively repair MR of all forms. This highly innovative and interdisciplinary project combines expertise in surgical robotics, imaging and mitral repair devices. We envision that the intravascular steerable robot and implant, guided by multimodality imaging will significantly simplify Transcatheter mitral valve repair, increasing the procedural accuracy and control, and reducing failure rates. [Learn more]
2018 - Poster Awards at the International Conference of SPIE Medical Imaging
James Dormer, a Research Engineer from Dr. Baowei Fei’s Lab, won two Poster Award – Honorable at the International Conference of SPIE Medical Imaging. The first award is from the SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging Conference. His paper is entitled “Heart chamber segmentation from CT using convolutional neural networks.” The second award is from the SPIE Medical Imaging: Ultrasonic Imaging and Tomography Conference. The title of his paper is “Ultrasound segmentation of rat hearts using a convolution neural network.” [Learn more]
James Dormer, a Research Engineer from Dr. Baowei Fei’s Lab, won two Poster Award – Honorable at the International Conference of SPIE Medical Imaging. The first award is from the SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging Conference. His paper is entitled “Heart chamber segmentation from CT using convolutional neural networks.” The second award is from the SPIE Medical Imaging: Ultrasonic Imaging and Tomography Conference. The title of his paper is “Ultrasound segmentation of rat hearts using a convolution neural network.” [Learn more]
2018 - Robert F. Wagner All Conferences Best Student Paper Award
Martin Halicek, a PhD student from Dr. Baowei Fei’s Lab, received the Robert F. Wagner All Conference Best Student Paper Award – Runner-Up at the International Conferences of SPIE Medical Imaging in Houston, Texas in February 12, 2018. The title of his paper is “Tumor margin classification of head and neck cancer using hyperspectral imaging and convolutional neural networks.” The Robert F. Wagner All Conference Best Student Paper Award (established 2014) is an acknowledgement of his many important contributions to the Medical Imaging meeting and his many important advances in the field of medical imaging and is co-sponsored The Medical Imaging Perception Society and SPIE. A first-place winner and runner-up were recognized with a cash prize ($1,000 and $500 respectively) and a certificate during the Plenary Session at the conference. [Learn more]
Martin Halicek, a PhD student from Dr. Baowei Fei’s Lab, received the Robert F. Wagner All Conference Best Student Paper Award – Runner-Up at the International Conferences of SPIE Medical Imaging in Houston, Texas in February 12, 2018. The title of his paper is “Tumor margin classification of head and neck cancer using hyperspectral imaging and convolutional neural networks.” The Robert F. Wagner All Conference Best Student Paper Award (established 2014) is an acknowledgement of his many important contributions to the Medical Imaging meeting and his many important advances in the field of medical imaging and is co-sponsored The Medical Imaging Perception Society and SPIE. A first-place winner and runner-up were recognized with a cash prize ($1,000 and $500 respectively) and a certificate during the Plenary Session at the conference. [Learn more]
2018 - Martin Halicek, an MD/PhD student in Dr. Fei’s Lab received the Robert Jones Award
The Jones Award creates opportunities for advancement in patient care and the discovery of cures. Through a unique collaboration between Emory University and Georgia Institute of Technology, the Jones Biomedical Engineering Fellows conduct groundbreaking research and lead the fight against debilitating diseases like Parkinson’s disease, Alzheimer’s disease, cancer, and syringomyelia, the rare neurological condition Jones suffered from at the end of his life. The Jones Award is to recognize a BME student in the Laney Graduate School at Emory University for exceptional research accomplishments as identified by the faculty. [Learn more]
The Jones Award creates opportunities for advancement in patient care and the discovery of cures. Through a unique collaboration between Emory University and Georgia Institute of Technology, the Jones Biomedical Engineering Fellows conduct groundbreaking research and lead the fight against debilitating diseases like Parkinson’s disease, Alzheimer’s disease, cancer, and syringomyelia, the rare neurological condition Jones suffered from at the end of his life. The Jones Award is to recognize a BME student in the Laney Graduate School at Emory University for exceptional research accomplishments as identified by the faculty. [Learn more]
2017 - Dr. Baowei Fei served on the NIH Study Section ZRG1 SBIB-F (59)R on Imaging and Biomarker for Early Detection of Aggressive Cancer
The purpose of this Funding Opportunity Announcement (FOA) is to: (i) invite researchers to submit collaborative research project (U01) applications to improve cancer screening, early detection of aggressive cancer, assessment of cancer risk and cancer diagnosis aimed at integrating multi-modality imaging strategies and multiplexed biomarker methodologies into a singular complementary approach, and (ii) establish a Consortium for Imaging and Biomarkers (CIB) to perform collaborative studies, exchange information, share knowledge and leverage common resources. The research will be conducted by individual multi-disciplinary research teams, hereafter called Units. All Units are expected to participate in collaborative activities with other Units within the Consortium. For more information about this funding program, please visit NIH Grants. [Learn more]
The purpose of this Funding Opportunity Announcement (FOA) is to: (i) invite researchers to submit collaborative research project (U01) applications to improve cancer screening, early detection of aggressive cancer, assessment of cancer risk and cancer diagnosis aimed at integrating multi-modality imaging strategies and multiplexed biomarker methodologies into a singular complementary approach, and (ii) establish a Consortium for Imaging and Biomarkers (CIB) to perform collaborative studies, exchange information, share knowledge and leverage common resources. The research will be conducted by individual multi-disciplinary research teams, hereafter called Units. All Units are expected to participate in collaborative activities with other Units within the Consortium. For more information about this funding program, please visit NIH Grants. [Learn more]
2017 - Dr. Baowei Fei was awarded a five-year NIH R01 grant
The project is to translate our positron emission tomography (PET)/transrectal ultrasound (TRUS) fusion guided technology into a commercially supported platform for improving the detection of prostate cancer. It has been reported that the long-term prostate cancer specific survival of patients initially managed with active surveillance (AS) or watchful waiting for low-risk prostate cancer ranges from 97% to 100%. However, among all men with indolent prostate cancer, the rate of aggressive treatment is as high as 64.3%. The costs for the treatment are $12 billion each year in the USA. One reason for aggressive treatment is due to the fact that the current standard diagnosis with transrectal ultrasound-guided biopsy can miss up to 30% of cancers. A major concern for active surveillance is the risk of high-grade cancer that may be missed by the current diagnosis. This research is to develop innovative imaging technology that can improve the detection rate and distinguish aggressive cancer, which requires treatment, from the non-aggressive disease, which can be well-managed with active surveillance. The technology will provide clinicians a new imaging tool to select millions of low-risk prostate cancer patients for active surveillance instead of unnecessary treatment, therefore may help save billions of dollars in treatment costs and improve the care of prostate cancer patients. [Learn more]
The project is to translate our positron emission tomography (PET)/transrectal ultrasound (TRUS) fusion guided technology into a commercially supported platform for improving the detection of prostate cancer. It has been reported that the long-term prostate cancer specific survival of patients initially managed with active surveillance (AS) or watchful waiting for low-risk prostate cancer ranges from 97% to 100%. However, among all men with indolent prostate cancer, the rate of aggressive treatment is as high as 64.3%. The costs for the treatment are $12 billion each year in the USA. One reason for aggressive treatment is due to the fact that the current standard diagnosis with transrectal ultrasound-guided biopsy can miss up to 30% of cancers. A major concern for active surveillance is the risk of high-grade cancer that may be missed by the current diagnosis. This research is to develop innovative imaging technology that can improve the detection rate and distinguish aggressive cancer, which requires treatment, from the non-aggressive disease, which can be well-managed with active surveillance. The technology will provide clinicians a new imaging tool to select millions of low-risk prostate cancer patients for active surveillance instead of unnecessary treatment, therefore may help save billions of dollars in treatment costs and improve the care of prostate cancer patients. [Learn more]
2016 - Workshop and Launch of the Integrative Cancer Imaging Research Program (iCIRP)
The Integrative Cancer Imaging Research Program (iCIRP) is a joint program between Emory University School of Medicine Department of Radiology and Imaging Sciences, Georgia Tech/Emory Coulter Department of Biomedical Engineering, and Winship Cancer Institute of Emory University. This program will build on and synergize unique strengths inherent in Emory units and centers that foster multidisciplinary collaborations within and among the disciplines of imaging science, cancer biology, nanotechnology, biomarker development, computation, and clinical cancer research. The overarching goal of the iCIRP program is to advance cancer detection, diagnosis, prognosis, image-guided therapy, prediction of efficacy, and monitoring of treatment. Dr. Baowei Fei’s talk on the introduction of the Program: PDF File For more information about this program, please visit: http://feilab.org/publication_pdf/Fei_iCIRP.pdf [Learn more]
The Integrative Cancer Imaging Research Program (iCIRP) is a joint program between Emory University School of Medicine Department of Radiology and Imaging Sciences, Georgia Tech/Emory Coulter Department of Biomedical Engineering, and Winship Cancer Institute of Emory University. This program will build on and synergize unique strengths inherent in Emory units and centers that foster multidisciplinary collaborations within and among the disciplines of imaging science, cancer biology, nanotechnology, biomarker development, computation, and clinical cancer research. The overarching goal of the iCIRP program is to advance cancer detection, diagnosis, prognosis, image-guided therapy, prediction of efficacy, and monitoring of treatment. Dr. Baowei Fei’s talk on the introduction of the Program: PDF File For more information about this program, please visit: http://feilab.org/publication_pdf/Fei_iCIRP.pdf [Learn more]
2016 - Dr. Baowei Fei served as Chair for NIH Study Section ZRG1 SBIB-F (56)R on Early Phase Clinical Trials in Imaging and Image-guided Interventions
This Funding Opportunity Announcement (FOA) is intended to support clinical trials conducting preliminary evaluation of the safety and efficacy of imaging agents, as well as an assessment of imaging systems, image processing, image-guided therapy, contrast kinetic modeling, 3-D reconstruction and other quantitative tools. As many such preliminary evaluations are early in development, this FOA will provide investigators with support for pilot (Phase I and II) cancer imaging clinical trials, including patient monitoring and laboratory studies. This FOA supports novel uses of known/standard clinical imaging agents and methods as well as the evaluation of new agents, systems, or methods. The imaging and image-guided intervention (IGI) investigations, if proven successful in these early clinical trials, can then be validated in larger studies through competitive R01 mechanisms, or through clinical trials in the Specialized Programs of Research Excellence (SPOREs), Cancer Centers and/or the NCI's National Clinical Trials Network. October 21, 2016 [Learn more]
This Funding Opportunity Announcement (FOA) is intended to support clinical trials conducting preliminary evaluation of the safety and efficacy of imaging agents, as well as an assessment of imaging systems, image processing, image-guided therapy, contrast kinetic modeling, 3-D reconstruction and other quantitative tools. As many such preliminary evaluations are early in development, this FOA will provide investigators with support for pilot (Phase I and II) cancer imaging clinical trials, including patient monitoring and laboratory studies. This FOA supports novel uses of known/standard clinical imaging agents and methods as well as the evaluation of new agents, systems, or methods. The imaging and image-guided intervention (IGI) investigations, if proven successful in these early clinical trials, can then be validated in larger studies through competitive R01 mechanisms, or through clinical trials in the Specialized Programs of Research Excellence (SPOREs), Cancer Centers and/or the NCI's National Clinical Trials Network. October 21, 2016 [Learn more]
2016 - Guolan Lu successfully defended her PhD thesis and joined Stanford University
As an emerging optical modality, hyperspectral imaging (HSI) holds great promise for early cancer detection and image-guided surgery. The major advantage of HSI is that it is a noninvasive technology that doesn't require any contrast agent, and it combines wide-field imaging and spectroscopy to simultaneously attain both spatial and spectral information from an object in a non-contact way. Light delivered to the tissue surface undergoes multiple elastic scattering and absorption interactions, and part of it returns as diffuse reflectance carrying diagnostic information about the underlying tissue structure and composition. The biochemical and morphological properties of the tissue change during disease progression. Therefore hyperspectral images, which contain high-dimensional spectral information at each image point, can be analyzed for visualization, characterization, and quantification of the disease state in biological tissue. The overall goal of this dissertation was to investigate the potential of label-free HSI technology combined with machine learning methods as a noninvasive diagnostic tool for quantitative detection and delineation of head and neck cancer. More specifically, this dissertation work has two applications: the early detection of cancer, and surgical guidance. To achieve this, we had four different aims. The first two aims evaluated the diagnostic performance of HSI and machine learning algorithms at differentiating cancer from normal tissue in preclinical animal models, including a subcutaneous cancer model (Aim 1), and a chemically-induced tongue carcinogenesis model (Aim 2). The last two aims investigated the detection and delineation of head and neck cancer in a surgical animal model (Aim 3) and fresh surgical specimens of human patients (Aim 4). [Learn more]
As an emerging optical modality, hyperspectral imaging (HSI) holds great promise for early cancer detection and image-guided surgery. The major advantage of HSI is that it is a noninvasive technology that doesn't require any contrast agent, and it combines wide-field imaging and spectroscopy to simultaneously attain both spatial and spectral information from an object in a non-contact way. Light delivered to the tissue surface undergoes multiple elastic scattering and absorption interactions, and part of it returns as diffuse reflectance carrying diagnostic information about the underlying tissue structure and composition. The biochemical and morphological properties of the tissue change during disease progression. Therefore hyperspectral images, which contain high-dimensional spectral information at each image point, can be analyzed for visualization, characterization, and quantification of the disease state in biological tissue. The overall goal of this dissertation was to investigate the potential of label-free HSI technology combined with machine learning methods as a noninvasive diagnostic tool for quantitative detection and delineation of head and neck cancer. More specifically, this dissertation work has two applications: the early detection of cancer, and surgical guidance. To achieve this, we had four different aims. The first two aims evaluated the diagnostic performance of HSI and machine learning algorithms at differentiating cancer from normal tissue in preclinical animal models, including a subcutaneous cancer model (Aim 1), and a chemically-induced tongue carcinogenesis model (Aim 2). The last two aims investigated the detection and delineation of head and neck cancer in a surgical animal model (Aim 3) and fresh surgical specimens of human patients (Aim 4). [Learn more]