most citedFoundation Models for Biomedical Image Segmentation: A Survey

14 citations · 17 across the 5 of their papers we have counts for

collaborators

6 papers

cs.DC2024★ 1 cited

Scalable quality control on processing of large diffusion-weighted and structural magnetic resonance imaging datasets

Michael E. Kim, Chenyu Gao, Karthik Ramadass +16

Proper quality control (QC) is time consuming when working with large-scale medical imaging datasets, yet necessary, as poor-quality data can lead to erroneous conclusions or poorl…

cs.DC2024★ 1 cited

Scalable, reproducible, and cost-effective processing of large-scale medical imaging datasets

Michael E. Kim, Karthik Ramadass, Chenyu Gao +11

Curating, processing, and combining large-scale medical imaging datasets from national studies is a non-trivial task due to the intense computation and data throughput required, va…

physics.med-ph2024

Harmonized connectome resampling for variance in voxel sizes

Elyssa M. McMaster, Nancy R. Newlin, Gaurav Rudravaram +10

To date, there has been no comprehensive study characterizing the effect of diffusion-weighted magnetic resonance imaging voxel resolution on the resulting connectome for high reso…

eess.IV2024★ 1 cited

Tractography with T1-weighted MRI and associated anatomical constraints on clinical quality diffusion MRI

Tian Yu, Yunhe Li, Michael E. Kim +8

Diffusion MRI (dMRI) streamline tractography, the gold standard for in vivo estimation of brain white matter (WM) pathways, has long been considered indicative of macroscopic relat…

q-bio.NC2024

Evaluation of Mean Shift, ComBat, and CycleGAN for Harmonizing Brain Connectivity Matrices Across Sites

Hanliang Xu, Nancy R. Newlin, Michael E. Kim +15

Connectivity matrices derived from diffusion MRI (dMRI) provide an interpretable and generalizable way of understanding the human brain connectome. However, dMRI suffers from inter…

cs.CV2024★ 14 cited

Foundation Models for Biomedical Image Segmentation: A Survey

Ho Hin Lee, Yu Gu, Theodore Zhao +9

Recent advancements in biomedical image analysis have been significantly driven by the Segment Anything Model (SAM). This transformative technology, originally developed for genera…