Skip to main content

Enabling Multi-shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE

Jan. 17, 2020—Nath V, Lyu I, Schilling KG, Parvathaneni P, Hansen CB, Huo Y, Janve VA, Gao Y, Stepniewska I, Anderson AW, Landman BA. Enabling Multi-shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2019 Oct 13 (pp. 573-581). Springer, Cham. Full text: https://arxiv.org/ftp/arxiv/papers/1907/1907.06319.pdf Abstract Intra-voxel...

Read more


Harmonizing 1.5 T/3T diffusion weighted MRI through development of deep learning stabilized microarchitecture estimators

Jan. 17, 2020—Nath V, Remedios S, Parvathaneni P, Hansen CB, Bayrak RG, Bermudez C, Blaber JA, Schilling KG, Janve VA, Gao Y, Huo Y. Harmonizing 1.5 T/3T diffusion weighted MRI through development of deep learning stabilized microarchitecture estimators. In Medical Imaging 2019: Image Processing 2019 Mar 15 (Vol. 10949, p. 109490O). International Society for Optics and Photonics....

Read more


Tractography reproducibility challenge with empirical data (TRAceD): The 2017 ISMRM diffusion study group challenge

Jan. 17, 2020—Nath V, Schilling KG, Parvathaneni P, Huo Y, Blaber JA, Hainline AE, Barakovic M, Romascano D, Rafael‐Patino J, Frigo M, Girard G. Tractography reproducibility challenge with empirical data (traced): The 2017 ISMRM diffusion study group challenge. Journal of Magnetic Resonance Imaging. 2020 Jan;51(1):234-49. Full text: https://www.ncbi.nlm.nih.gov/pubmed/31179595 Abstract BACKGROUND: Fiber tracking with diffusion-weighted MRI has become an...

Read more


Deep learning reveals untapped information for local white-matter fiber reconstruction in diffusion-weighted MRI

Jan. 17, 2020—Nath V, Schilling KG, Parvathaneni P, Hansen CB, Hainline AE, Huo Y, Blaber JA, Lyu I, Janve V, Gao Y, Stepniewska I, Anderson AW, Landman BA. Deep learning reveals untapped information for local white-matter fiber reconstruction in diffusion-weighted MRI. Magnetic resonance imaging. 2019 Oct 1;62:220-7. Abstract PURPOSE: Diffusion-weighted magnetic resonance imaging (DW-MRI) is of critical importance...

Read more


Extracting 2D weak labels from volume labels using multiple instance learning in CT hemorrhage detection

Jan. 2, 2020—Remedios, S. W., Wu, Z., Bermudez, C., Kerley, C. I., Roy, S., Patel, M. B., Butman, J. A., Landman, B. A., Pham, D. L. (2019). Extracting 2D weak labels from volume labels using multiple instance learning in CT hemorrhage detection. arXiv preprint arXiv:1911.05650. Full Text: Arxiv Link Abstract Multiple instance learning (MIL) is a supervised learning methodology...

Read more


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...

Read more


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...

Read more


Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision

Dec. 19, 2019—Ho Hin Lee, Yucheng Tang, Olivia Tang, Yuchen Xu, Yunqiang Chen, Dashan Gao, Shizhong Han, Riqiang Gao, Michael R. Savona, Richard G. Abramson, Yuankai Huo, Bennett A. Landman, “Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision”, SPIE MI:IP 2020. Houston, TX. Link: https://arxiv.org/abs/1911.05113 Abstract Human in-the-loop quality assurance (QA) is typically performed after medical image segmentation to ensure that...

Read more


Diffusion MRI microstructural models in the cervical spinal cord – application, normative values, and correlations with histological analysis

Dec. 16, 2019—Kurt G. Schilling, Samantha By, Haley Feiler, Bailey Box, Kristin P. O’Grady, Atlee Witt, Bennett A. Landman, Seth A. Smith. “Diffusion MRI microstructural models in the cervical spinal cord – application, normative values, and correlations with histological analysis”. NeuroImage. doi: 10.1016/j.neuroimage.2019.116026. 2019. Full text: https://www.ncbi.nlm.nih.gov/pubmed/31326569 Abstract Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven...

Read more


Synthesized b0 for diffusion distortion correction (Synb0-DisCo).

Dec. 16, 2019—Kurt G Schilling, Yuankai Huo, Allen Newton, Colin Hansen, Vishwesh Nath, Andrea T. Shafer, Owen Williams, Susan M. Resnick, Baxter Rogers, Adam W Anderson, Bennett A Landman. “Synthesized b0 for diffusion distortion correction (Synb0-DisCo).” Magnetic Resonance Imaging. 2019 May 7. pii: S0730-725X(18)30617-9. doi: 10.1016/j.mri.2019.05.008 Full text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Synthesized+b0+for+diffusion+distortion+correction+(Synb0-DisCo). Abstract Diffusion magnetic resonance images typically suffer from spatial...

Read more