Image Processing Category
Vasculature-informed spatial smoothing of white matter functional magnetic resonance imaging
Apr. 18, 2025—Adam M. Saunders, Michael E. Kim, Kurt G. Schilling, John C. Gore, Bennett A. Landman, and Yurui Gao. Vasculature-informed spatial smoothing of white matter functional magnetic resonance imaging. SPIE Medical Imaging: Image Processing, 2025, February, San Diego, California. https://doi.org/10.1117/12.3047240. Abstract Blood oxygenation level-dependent (BOLD) signals in white matter in the brain are anisotropically oriented, so...
A 4D atlas of diffusion-informed spatial smoothing windows for BOLD signal in white matter
Apr. 18, 2025—Adam M. Saunders, Gaurav Rudravaram, Nancy R. Newlin, Michael E. Kim, John C. Gore, Bennett A. Landman, and Yurui Gao. A 4D atlas of diffusion–informed spatial smoothing windows for BOLD signal in white matter. SPIE Medical Imaging: Image Processing, 2025, February, San Diego, California. https://doi.org/10.1117/12.3047240 Abstract Typical methods for preprocessing functional magnetic resonance images (fMRI)...
Comparison and calibration of MP2RAGE quantitative T1 values to multi-TI inversion recovery T1 values
Apr. 13, 2025—Adam M. Saunders, Michael E. Kim, Chenyu Gao, Lucas W. Remedios, Aravind R. Krishnan, Kurt G. Schilling, Kristin P. O’Grady, Seth A. Smith, and Bennett A. Landman. Comparison and calibration of MP2RAGE quantitative T1 values to multi-TI inversion recovery T1 values. Magnetic Resonance Imaging, 2025; 117:110322. https://doi.org/10.1016/j.mri.2025.110322. Abstract While typical qualitative T1-weighted magnetic resonance images...
Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks
Apr. 24, 2024—Aravind R. Krishnan, Kaiwen Xu, Thomas Li, Lucas W. Remedios, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman. “Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.”Med Phys. 2024;1-14.https://doi.org/10.1002/mp.17028 Abstract Background The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction...
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...
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....
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,...
Reproducibility evaluation of the effects of MRI defacing on brain segmentation
Nov. 10, 2023—Chenyu Gao, Bennett A. Landman, Jerry L. Prince, Aaron Carass. “Reproducibility evaluation of the effects of MRI defacing on brain segmentation”. J. Med. Imag. 10(6), 064001 (2023), https://doi.org/10.1117/1.JMI.10.6.064001, [PDF] Abstract Purpose Recent advances in magnetic resonance (MR) scanner quality and the rapidly improving nature of facial recognition software have necessitated the introduction of MR defacing...