Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
Aug. 28, 2021—Riqiang Gao, Yucheng Tang, Kaiwen Xu, Ho Hin Lee, Steve Deppen, Kim Sandler, Pierre Massion, Thomas A. Lasko, Yuankai Huo, Bennett A. Landman, Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective, MICCAI, 2021. Full text: https://arxiv.org/abs/2107.11882 Abstract Data from multi-modality provide complementary information in clinical prediction, but missing data in clinical cohorts limits...
Technical Note: Comparison of Convolutional Neural Networks for Detecting Large Vessel Occlusion on Computed Tomography Angiography
Jul. 21, 2021—Lucas W. Remedios, Sneha Lingam, Samuel W. Remedios, Riqiang Gao, Stephen W. Clark, Larry T. Davis, Bennett A. Landman. Technical Note: Comparison of Convolutional Neural Networks for Detecting Large Vessel Occlusion on Computed Tomography Angiography. Medical Physics, 2021 Full Text Abstract Purpose: Artificial intelligence diagnosis and triage of large vessel occlusion may quicken clinical response for...
PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images
Jun. 23, 2021—Leon Y. Cai, Qi Yang, Colin B. Hansen, Vishwesh Nath, Karthik Ramadass, Graham W. Johnson, Benjamin N. Conrad, Brian D. Boyd, John P. Begnoche, Lori L. Beason-Held, Andrea T. Shafer, Susan M. Resnick, Warren D. Taylor, Gavin R. Price, Victoria L. Morgan, Baxter P. Rogers, Kurt G. Schilling, Bennett A. Landman. PreQual: An automated pipeline...
Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training
Apr. 1, 2021—Ilwoo Lyu, Shunxing Bao, Lingyan Hao, Jewelia Yao, Jacob Miller, Willa Voorhies, Warren Taylor, Silvia Bunge, Kevin Weiner, Bennett Landman. “Labeling Lateral Prefrontal Sulci using Spherical Data Augmentation and Context-aware Training”. NeuroImage, 229, 117758, 2021. [Full text][Code] Abstract The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow...
Body Part Regression With Self-Supervision
Jan. 14, 2021—Y.Tang, R.Gao, S.Han, Y.Chen, D.Gao, V.Nath, C.Bermudez, M.R. Savona, R.G. Abramson, S.Bao,I.Lyu, Y.Huo and B.A. Landman,”Body Part Regression with Self-supervision”,IEEETransactions onMedicalImaging,2021 Full Text: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9350603 Abstract Body part regression is a promising new technique that enables content navigation through selfsupervised learning. Using this technique, the global quantitative spatial location for each axial view slice is obtained...
RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior
Dec. 28, 2020—Ho Hin Lee, Yucheng Tang, Shunxing Bao, Richard G. Abramson, Yuankai Huo, Bennett A. Landman. “RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior.” arXiv preprint arXiv:2012.12425 (2020). Full Text Abstract Performing coarse-to-fine abdominal multi-organ segmentation facilitates to extract high-resolution segmentation minimizing the lost of spatial contextual information. However, current coarse-to-refine approaches require a significant number of models...
Multi-Contrast Computed Tomography Healthy Kidney Atlas
Dec. 28, 2020—Ho Hin Lee, Yucheng Tang, Kaiwen Xu, Shunxing Bao, Agnes B. Fogo, Raymond Harris, Mark P. de Caestecker, Mattias Heinrich, Jeffery M. Spraggins, Yuankai Huo, Bennett A. Landman, “Multi-Contrast Computed Tomography Healthy Kidney Atlas.” arXiv preprint arXiv:2012.12432 (2020). Full Text Abstract The construction of three-dimensional multi-modal tissue maps provides an opportunity to spur interdisciplinary innovations across temporal and...
Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning
Dec. 26, 2020—Bermudez, C., Remedios, S. W., Ramadass, K., McHugo, M., Heckers, S., Huo, Y., & Landman, B. A. (2020). Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning. Journal of Medical Imaging, 7(6), 064004. Full Text: https://pubmed.ncbi.nlm.nih.gov/33381612/ Abstract Purpose: Generalizability is an important problem in deep neural networks, especially with variability of data acquisition in...
Challenges for biophysical modeling of microstructure
Dec. 9, 2020—Ileana O. Jelescu, Marco Palombo, Francesca Bagnato, Kurt G. Schilling. “Challenges for biophysical modeling of microstructure”. (2020) Journal of Neuroscience Methods 108861. Full text: https: https://www.sciencedirect.com/science/article/pii/S0165027020302843 Abstract The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of...
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...