Deep 3D convolutional neural networks for fast super-resolution ultrasound imaging

Brown K, Dormer JD, Fei BW, Hoyt K, Ruiter NV, Byram BC. Deep 3D convolutional neural networks for fast super-resolution ultrasound imaging. Proceedings of SPIE Medical Imaging 2019: Ultrasonic Imaging and Tomography.

Phase asymmetry guided adaptive fractional-order total variation and diffusion for feature-preserving ultrasound despeckling

Mei KQ, Hu B, Fei BW, Qin BJ. Phase asymmetry guided adaptive fractional-order total variation and diffusion for feature-preserving ultrasound despeckling. arXiv:1810.12538.

Heart chamber segmentation from CT using convolutional neural networks

Dormer JD, Ma L, Halicek M, Reilly CM, Schreibmann E, Fei BW (Corresponding author). Heart chamber segmentation from CT using convolutional neural networks. Proceedings of SPIE: The International Society for Optical Engineering;10578.

Convolutional neural networks for the detection of diseased hearts using CT images and left atrium patches

Dormer JD, Halicek M, Ma L, Reilly CM, Schreibmann E, Fei BW (Corresponding author). Convolutional neural networks for the detection of diseased hearts using CT images and left atrium patches. Proceedings of SPIE: The International Society for Optical Engineering;10575.

The role of fluciclovine (18F) PET/CT directed, 3D ultrasound-guided fusion targeted biopsy in the detection of biochemically recurrent prostate cancer

Abiodun-Ojo OA, Fei BW Nieh PT, Master VA, Akintayo A, Tade F, Akin-Akintayo O, Alemozaffar M, Osunkoya AO, Goodman MM, Schuster DM. The role of fluciclovine (18F) PET/CT directed, 3D ultrasound-guided fusion targeted biopsy in the detection of biochemically recurrent prostate cancer. Journal of Nuclear Medicine;59(s1):1481.

Cardiac Fiber Imaging with 3D Ultrasound and MR Diffusion Tensor Imaging

Qin X, Fei BW. “Cardiac Fiber Imaging with 3D Ultrasound and MR Diffusion Tensor Imaging.” In Cardiovascular Imaging: An Engineering and Clinical Perspective, edited by Ayman El-Baz. Boca Raton, FL: CRC Press, Taylor & Francis Group, 2018.

A supervoxel-based segmentation method for prostate MR images

Tian, ZQ., Liu, LZ., Zhang, ZF., Xue, JR., Fei, BW.(2017). “A supervoxel-based segmentation method for prostate MR images.”Medical Physics 44(2): 558-569.

A random walk‐based segmentation framework for 3D ultrasound images of the prostate

*Ma L, Guo R, Zhang G, Fei BW (Corresponding author). “A random walk‐based segmentation framework for 3D ultrasound images of the prostate,”Medical Physics, 2017 Jun 5. doi: 10.1002/mp.12396. [Epub ahead of print] PubMed PMID:28582803 (*Ph.D. Student) 2017.

A Combined Learning Algorithm for Prostate Segmentation on 3D CT Images

*Ma L, Guo R, Zhang G, Schuster, DM, Fei BW (Corresponding author). “A Combined Learning Algorithm for Prostate Segmentation on 3D CT Images,”Medical Physics, (In Press, *Ph.D. Student) 2017.

Learning with distribution of optimized features for recognizing common CT imaging signs of lung diseases

*Ma L, Liu X, Fei BW (Corresponding author). Learning with distribution of optimized features for recognizing common CT imaging signs of lung diseases, Physics in Medicine and Biology 2017, 62:612-632. (*Ph.D. Student)