Hyperspectral imaging in medical applications

/in

Fei BW. Hyperspectral imaging in medical applications. Data Handling in Science and Technology; 32: 523-565. Elsevier,

18F-Fluciclovine parameters on targeted prostate biopsy associated with true positivity in recurrent prostate cancer

/in ,

Abiodun-Ojo OA, Akintayo AA, Akin-Akintayo O, Tade FI, Nieh PT, Master VA, Alemozaffar M, Osunkoya AO, Goodman MM, Fei BW (Corresponding author). 18F-Fluciclovine parameters on targeted prostate biopsy associated with true positivity in recurrent prostate cancer. Journal of Nuclear Medicine; 60(11): 1531-1536.

Adaptive deep learning for head and neck cancer detection using hyperspectral imaging

/in

Ma L, Lu G, Wang D, Qin X, Chen ZG, Fei BW (Corresponding author). Adaptive deep learning for head and neck cancer detection using hyperspectral imaging. Visual Computing for Industry, Biomedicine, and Art; 2(1): 1-12.

A semiautomatic approach for prostate segmentation in MR images using local texture classification and statistical shape modeling

/in

Shahedi M, Halicek M, Li QM, Lizhi L, Zhang ZF, Verma S, Schuster DM, Fei BW (Corresponding author). A semiautomatic approach for prostate segmentation in MR images using local texture classification and statistical shape modeling. Proceedings of SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling.

Cancer detection using hyperspectral imaging and evaluation of the superficial tumor margin variance with depth

/in ,

Halicek M, Himar F, Ortega S, Little JV, Wang X, Chen AY, Callicó GM, Myers LL, Sumer BD, Fei BW (Corresponding author). Cancer detection using hyperspectral imaging and evaluation of the superficial tumor margin variance with depth. Proceedings of SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling.

Classification of brain tumor IDH status using MRI and deep learning

/in

Nalawade SS, Muregesan GK, Vejdani-Jahromi M, Fisicaro RA, Yogananda CGB, Wagner B, Mickey B, Maher E, Pinho MC, Fei BW. Classification of Brain Tumor IDH Status using MRI and Deep Learning. bioRxiv (2019):757344.

Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning

/in ,

Nalawade S, Murugesan GK, Vejdani-Jahromi M, Fisicaro RA, Yogananda GCB, Wagner B, Mickey B, Maher E, Pinho MC, Fei BW, Madhuranthakam AJ, Maldjian JA. Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning. Journal of Medical Imaging; 6(4): 046003.

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

/in

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.

Deep learning-based framework for in-vivo identification of glioblastoma tumor using hyperspectral images of human brain

/in ,

Fabelo H, Halicek M, Ortega S, Shahedi M, Szolna A, Pineiro JF, Sosa C, O’Shanahan AJ, Bisshopp S, Espino C, Marquez M, Hernandez M, Carrera D, Morera J, Callicó GM, Sarmiento R, Fei BW (Corresponding author). Deep learning-based framework for in-vivo identification of glioblastoma tumor using hyperspectral images of human brain. Sensors;19(4).

Deep learning-based three-dimensional segmentation of the prostate on computed tomography images

/in

Shahedi M, Halicek M, Dormer JD, Schuster DM, Fei BW (Corresponding author). Deep learning-based three-dimensional segmentation of the prostate on computed tomography images. Journal of Medical Imaging;6(2):025003.