Deep Learning Category
Time-Distanced Gates in Long Short-Term Memory Networks
Nov. 25, 2020—Gao, R., Tang, Y., Xu, K., Huo, Y., Bao, S., Antic, S.L., Epstein, E.S., Deppen, S., Paulson, A.B., Sandler, K.L. and Massion, P.P., Landman, B. A., Time-distanced gates in long short-term memory networks. Medical Image Analysis, 2020. Full Text: https://pubmed.ncbi.nlm.nih.gov/32745977/ Abstract The Long Short-Term Memory (LSTM) network is widely used in modeling sequential observations in fields ranging...
Renal Cortex, Medulla and Pelvicaliceal System Segmentation on Arterial Phase CT Images with Random Patch-based Networks
Nov. 21, 2020—Yucheng Tang, Riqiang Gao, Ho Hin Lee, Brent V. Savoie, Shunxing Bao, Yuankai Huo, Jeffrey Spraggins and Bennett A, Landman, Renal Cortex, Medulla, Pelvis Segmentation on Arterial Phase CT Images with Random Patch-based Networks, SPIE 2021 Medical Imaging Full Text Abstract Renal segmentation on contrast-enhanced computed tomography (CT) provides distinct spatial context and morphology. Current studies for renal segmentations...
Automatic Labeling of Cortical Sulci using Convolutional Neural Networks in a Developmental Cohort
Apr. 20, 2020—Lingyan Hao, Shunxing Bao, Yucheng Tang, Riqiang Gao, Prasanna Parvathaneni, Jacob Miller, Willa Voorhies, Jewelia Yao, Silvia Bunge, Kevin Weiner, Bennett Landman, Ilwoo Lyu. “Automatic Labeling of Cortical Sulci using Convolutional Neural Networks in a Developmental Cohort”. IEEE International Symposium on Biomedical Imaging (ISBI) 2020, IEEE, 412-415, Iowa City, Iowa, USA, 2020. [Full text][Code] Abstract...
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...
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....
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...
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...
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...
Using deep learning for a diffusion-based segmentation of the dentate nucleus and its benefits over atlas-based methods
Dec. 6, 2019—Noguera, C. B., Bao, S., Petersen, K. J., Lopez, A. M., Reid, J., Plassard, A. J., … & Landman, B. A. (2019). Using deep learning for a diffusion-based segmentation of the dentate nucleus and its benefits over atlas-based methods. Journal of Medical Imaging, 6(4), 044007. Full Text: https://www.ncbi.nlm.nih.gov/pubmed/31824980 Abstract The dentate nucleus (DN) is a...