December, 2023
Enhancing Hierarchical Transformers for Whole Brain Segmentation with Intracranial Measurements Integration
Dec. 20, 2023—Xin Yu, Yucheng Tang, Qi Yang, Ho Hin Lee, Shunxing Bao, Yuankai Huo, and Bennett A. Landman. “Enhancing Hierarchical Transformers for Whole Brain Segmentation with Intracranial Measurements Integration.” SPIE Medical Imaging 2024 Full text: NIHMSID Abstract: Whole brain segmentation with magnetic resonance imaging (MRI) enables the non-invasive measurement of brain regions, including total intracranial volume (TICV) and...
Nucleus subtype classification using inter-modality learning
Dec. 19, 2023—Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios, Ho Hin Lee, Leon Y. Cai, Thomas Li, Ruining Deng, Can Cui, Jia Li, Qi Liu, Ken S. Lau, Joseph T. Roland, Mary K. Washington, Lori A. Coburn, Keith T. Wilson, Yuankai Huo, Bennett A. Landman (2024). Nucleus subtype classification using inter-modality learning. SPIE Medical Imaging 2024 :...
Exploring shared memory architectures for end-to-end gigapixel deep learning
Dec. 19, 2023—Lucas W. Remedios, Leon Y. Cai, Samuel W. Remedios, Karthik Ramadass, Aravind Krishnan, Ruining Deng, Can Cui, Shunxing Bao, Lori A. Coburn, Yuankai Huo, Bennett A. Landman (2023). Exploring shared memory architectures for end-to-end gigapixel deep learning. MIDL 2023 short paper track Full text: NIHMSID Abstract Deep learning has made great strides in medical imaging, enabled by hardware advances in GPUs. One major constraint for the development...
Longitudinal Multimodal Transformer Integrating Imaging and Latent Clinical Signatures from Routine EHRs for Pulmonary Nodule Classification.
Dec. 13, 2023—Thomas Z. Li, John M. Still, Kaiwen Xu, Ho Hin Lee, Leon Y. Cai, Aravind R. Krishnan, Riqiang Gao, Mirza S. Khan, Sanja Antic, Michael Kammer, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman, Thomas A. Lasko. Abstract The accuracy of predictive models for solitary pulmonary nodule (SPN) diagnosis can be greatly increased by...
Nonlinear Gradient Field Estimation in Diffusion MRI Tensor Simulation
Dec. 8, 2023—Praitayini Kanakaraj, Tianyuan Yao, Nancy R. Newlin, Leon Y. Cai, Kurt G. Schilling, Baxter P. Rogers, Adam Anderson, Daniel Moyer, Bennett A. Landman. “Nonlinear Gradient Field Estimation in Diffusion MRI Tensor Simulation”. Physics of Medical Imaging SPIE 2024. Accepted Abstract Gradient nonlinearities not only induce spatial distortion in magnetic resonance imaging (MRI), but also introduce...
Identification of functional white matter networks in BOLD fMRI
Dec. 6, 2023—Alexa L. Eby, Lucas W. Remedios, Michael E. Kim, Muwei Li, Yurui Gao, John C. Gore, Kurt G. Schilling, Bennett A. Landman “Identification of functional white matter networks in BOLD fMRI” Full Text Abstract White matter signals in resting state blood oxygen level dependent functional magnetic resonance (BOLD-fMRI) have been largely discounted, yet there is...
Inter-vendor harmonization of CT reconstruction kernels using unpaired image translation
Dec. 1, 2023—Aravind R. Krishnan, Kaiwen Xu, Thomas Li, Chenyu Gao, Lucas W. Remedios, Praitayini Kanakaraj, Ho Hin Lee, Shunxing Bao, Kim L. Sandler, Fabien Maldonado, Ivana Išgum, and Bennett A. Landman “Inter-vendor harmonization of CT reconstruction kernels using unpaired image translation”, Proc. SPIE 12926, Medical Imaging 2024: Image Processing, 129261D (2 April 2024); https://doi.org/10.1117/12.3006608 Abstract The reconstruction kernel in computed tomography (CT) generation determines the texture of the image. Consistency...
Predicting Age from White Matter Diffusivity with Residual Learning
Dec. 1, 2023—Chenyu Gao, Michael E. Kim, Ho Hin Lee, Qi Yang, Nazirah Mohd Khairi, Praitayini Kanakaraj, Nancy R. Newlin, Derek B. Archer, Angela L. Jefferson, Warren D. Taylor, Brian D. Boyd, Lori L. Beason-Held, Susan M. Resnick, The BIOCARD Study Team, Yuankai Huo, Katherine D. Van Schaik, Kurt G. Schilling, Daniel Moyer, Ivana Išgum, Bennett A....
Characterizing Low-cost Registration for Photographic Images to Computed Tomography
Dec. 1, 2023—Michael E. Kim, Ho Hin Lee, Karthik Ramadass, Chenyu Gao, Katherine Van Schaik, Eric Tkaczyk, Jeffrey Spraggins, Daniel C. Moyer, Bennett A. Landman Biorxiv Link: https://www.biorxiv.org/content/10.1101/2023.09.22.558989v1 Figure 1. We map surfaces of phantom objects obtained from low-cost photogrammetry to surfaces obtained from volumetric CT scans of the phantoms in order to examine if similar...
Learning site-invariant features of connectomes to harmonize complex network measures
Dec. 1, 2023—Figure 1. Previous research elucidated that connectomes suffer from confounding site effects. In this work we propose a data-driven model to learn disjoint site (𝑐 = {1,2}) and biological features (siteless z) for BIOCARD (orange) and VMAP (blue) (left). We then inject a prescribed site, c’, to the learned representations to compute harmonized connectome modularity,...