Big Data Category
Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records
Dec. 7, 2020—Yucheng Tang, Riqiang Gao, Ho Hin Lee, Quinn Stanton Wells, Ashley Spann, James Gregory Terry, Jeff Carr, Yuankai Huo, Shunxing Bao and Bennett A. Landman, “Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records”, MICCAI CLIP, 2020. Full Text: Abstract Type II diabetes mellitus (T2DM) is a significant public health concern...
Learning from dispersed manual annotations with an optimized data weighting policy
Dec. 7, 2020—Yucheng Tang, Riqiang Gao, Yunqiang Chen, Dashan Gao, Michael R. Savona, Richard G. Abramson, Shunxing Bao, Yuankai Huo and Bennett A. Landman, “Learning from Dispersed Manual Annotations with an Optimized Data Weighting Policy”, Journal of Medical Imaging, 2020. Full Text: Abstract https://pubmed.ncbi.nlm.nih.gov/32775501/ Purpose: Deep learning methods have become essential tools for quantitative interpretation of medical...
A cross-platform informatics system for the Gut Cell Atlas: integrating from clinical, anatomical and histological data
Dec. 6, 2020—Shunxing Bao, Sophie Chiron, Yucheng Tang, Cody N. Heiser, Austin N. Southard-Smith, Ho Hin Lee, Marisol A. Ramirez, Yuankai Huo, Mary K. Washington, Elizabeth A. Scoville, Joseph T. Roland, Qi Liu, Ken S. Lau, Keith T. Wilson, Lori A. Coburn, Bennett A. Landman, A cross-platform informatics system for the Gut Cell Atlas: integrating from clinical,...
Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography
Nov. 29, 2020—Colin B. Hansen, Qi Yang, Ilwoo Lyu, Francois Rheault, Cailey Kerley, Bramsh Qamar Chandio, Shreyas Fadnavis, Owen Williams, Andrea T. Shafer, Susan M. Resnick, David H. Zald, Laurie E. Cutting, Warren D. Taylor, Brian Boyd, Eleftherios Garyfallidis, Adam W. Anderson, Maxime Descoteaux, Bennett A. Landman, Kurt G. Schilling. Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography. Neuroinform (2020). Full Text Abstract Brain atlases have proven to be valuable neuroscience tools for...
Distributed Deep Learning Across Multisite Datasets for Generalized CT Hemorrhage Segmentation
Jan. 2, 2020—Remedios, S. W., Roy, S., Bermudez, C., Patel, M. B., Butman, J. A., Landman, B. A., & Pham, D. L. (2019). Distributed Deep Learning Across Multi‐site Datasets for Generalized CT Hemorrhage Segmentation. Medical physics. Full Text: Pubmed Link Abstract Purpose: As deep neural networks achieve more success in the wide field of computer vision, greater emphasis is...
Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury
Jan. 2, 2020—Remedios, Samuel, et al. “Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury.” Medical Imaging 2019: Image Processing. Vol. 10949. International Society for Optics and Photonics, 2019. Full text: PubMed Link Abstract Machine learning models are becoming commonplace in the domain of medical imaging, and with these methods comes an ever-increasing need...
Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Contrast MRI with Augmented Transfer Learning
Aug. 13, 2019—Bermudez, C., Blaber, J., Remedios, S.W., Reynolds, J.E., Lebel, C., McHugo, M., Heckers, S., Huo, Y., Landman, B.A. Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Constrast MRI with Augmented Transfer Learning. SPIE Medical Imaging: Image Processing 2020. Houston, TX. Full Text: NIHMSID Abstract Generalizability is an important problem in deep neural networks, especially in...
Anatomical context improves deep learning on the brain age estimation task
Jul. 12, 2019—Bermudez, C., Plassard, A. J., Chaganti, S., Huo, Y., Aboud, K. E., Cutting, L. E., … & Landman, B. A. (2019). Anatomical context improves deep learning on the brain age estimation task. Magnetic Resonance Imaging. Full Text: https://www.ncbi.nlm.nih.gov/pubmed/31247249 Abstract Deep learning has shown remarkable improvements in the analysis of medical images without the need for...
Montage based 3D Medical Image Retrieval from Traumatic Brain Injury Cohort using Deep Convolutional Neural Network
Dec. 10, 2018—Cailey I. Kerley, Yuankai Huo, Shikha Chaganti, Shunxing Bao, Mayur B. Patel, Bennett A. Landman. “Montage based 3D Medical Image Retrieval from Traumatic Brain Injury Cohort using Deep Convolutional Neural Network.” In SPIE Medical Imaging, International Society for Optics and Photonics, 2019. Full text: NIHMSID Abstract Brain imaging analysis on clinically acquired computed tomography (CT) is essential...
Technology Enablers for Big Data, Multi-Stage Analysis in Medical Image Processing
Oct. 26, 2018—Shunxing Bao, Prasanna Parvathaneni, Yuankai Huo, Yogesh Barve, Andrew J. Plassard, Yuang Yao, Hongyang Sun, Ilwoo Lyu, David H. Zald, Bennett A. Landman and Aniruddha Gokhale. “Technology Enablers for Big Data, Multi-Stage Analysis in Medical Image Processing.” Big Data (Big Data), 2018 IEEE International Conference. (accepted) (acceptance rate 18.9%) Full text: TBD Abstract Big data medical image processing...