activity
20202025
most citedSegment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

97 citations · 133 across the 38 of their papers we have counts for

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18 papers · 1 filter

cs.CV2025

Fine-grained Multi-class Nuclei Segmentation with Molecular-empowered All-in-SAM Model

Xueyuan Li, Can Cui, Ruining Deng +7

Purpose: Recent developments in computational pathology have been driven by advances in Vision Foundation Models, particularly the Segment Anything Model (SAM). This model facilita…

cs.CV2025

Lifespan Pancreas Morphology for Control vs Type 2 Diabetes using AI on Largescale Clinical Imaging

Lucas W. Remedios, Chloe Cho, Trent M. Schwartz +11

Purpose: Understanding how the pancreas changes is critical for detecting deviations in type 2 diabetes and other pancreatic disease. We measure pancreas size and shape using morph…

cs.CV2025★ 1 cited

Data-Driven Abdominal Phenotypes of Type 2 Diabetes in Lean, Overweight, and Obese Cohorts

Lucas W. Remedios, Chloe Cho, Trent M. Schwartz +10

Purpose: Although elevated BMI is a well-known risk factor for type 2 diabetes, the disease's presence in some lean adults and absence in others with obesity suggests that detailed…

cs.CV2025

Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel Optimization

Ho Hin Lee, Quan Liu, Shunxing Bao +2

Large kernel convolutions offer a scalable alternative to vision transformers for high-resolution 3D volumetric analysis, yet naively increasing kernel size often leads to optimiza…

cs.CV2025

Enhanced Feature-based Image Stitching for Endoscopic Videos in Pediatric Eosinophilic Esophagitis

Juming Xiong, Muyang Li, Ruining Deng +5

Video endoscopy represents a major advance in the investigation of gastrointestinal diseases. Reviewing endoscopy videos often involves frequent adjustments and reorientations to p…

cs.CV2025

Robust Body Composition Analysis by Generating 3D CT Volumes from Limited 2D Slices

Lianrui Zuo, Xin Yu, Dingjie Su +7

Body composition analysis provides valuable insights into aging, disease progression, and overall health conditions. Due to concerns of radiation exposure, two-dimensional (2D) sin…

cs.CV2025

Beyond the Lungs: Extending the Field of View in Chest CT with Latent Diffusion Models

Lianrui Zuo, Kaiwen Xu, Dingjie Su +8

The interconnection between the human lungs and other organs, such as the liver and kidneys, is crucial for understanding the underlying risks and effects of lung diseases and impr…

cs.CV2024★ 3 cited

Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease

Chenyu Gao, Michael E. Kim, Karthik Ramadass +27

Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting ea…

cs.CV2024★ 1 cited

Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI

Lucas W. Remedios, Han Liu, Samuel W. Remedios +7

Multimodal fusion promises better pancreas segmentation. However, where to perform fusion in models is still an open question. It is unclear if there is a best location to fuse inf…

cs.CV2024★ 1 cited

Multi-Modality Conditioned Variational U-Net for Field-of-View Extension in Brain Diffusion MRI

Zhiyuan Li, Chenyu Gao, Praitayini Kanakaraj +13

An incomplete field-of-view (FOV) in diffusion magnetic resonance imaging (dMRI) can severely hinder the volumetric and bundle analyses of whole-brain white matter connectivity. Al…

cs.CV2024★ 2 cited

Persistence Image from 3D Medical Image: Superpixel and Optimized Gaussian Coefficient

Yanfan Zhu, Yash Singh, Khaled Younis +2

Topological data analysis (TDA) uncovers crucial properties of objects in medical imaging. Methods based on persistent homology have demonstrated their advantages in capturing topo…

cs.CV2024★ 4 cited

Field-of-View Extension for Brain Diffusion MRI via Deep Generative Models

Chenyu Gao, Shunxing Bao, Michael Kim +13

Purpose: In diffusion MRI (dMRI), the volumetric and bundle analyses of whole-brain tissue microstructure and connectivity can be severely impeded by an incomplete field-of-view (F…

cs.CV2024

Nucleus subtype classification using inter-modality learning

Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios +14

Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available b…

cs.CV2023★ 3 cited

DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable Convolution

Ho Hin Lee, Quan Liu, Qi Yang +4

The application of 3D ViTs to medical image segmentation has seen remarkable strides, somewhat overshadowing the budding advancements in Convolutional Neural Network (CNN)-based mo…

cs.CV2023★ 2 cited

All-in-SAM: from Weak Annotation to Pixel-wise Nuclei Segmentation with Prompt-based Finetuning

Can Cui, Ruining Deng, Quan Liu +5

The Segment Anything Model (SAM) is a recently proposed prompt-based segmentation model in a generic zero-shot segmentation approach. With the zero-shot segmentation capacity, SAM…

cs.CV2023

Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures

Shunxing Bao, Sichen Zhu, Vasantha L Kolachala +16

Crohn's disease (CD) is a chronic and relapsing inflammatory condition that affects segments of the gastrointestinal tract. CD activity is determined by histological findings, part…

cs.CV2023

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

Can Cui, Yaohong Wang, Shunxing Bao +11

Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during train…

cs.CV2023

Exploring shared memory architectures for end-to-end gigapixel deep learning

Lucas W. Remedios, Leon Y. Cai, Samuel W. Remedios +8

Deep learning has made great strides in medical imaging, enabled by hardware advances in GPUs. One major constraint for the development of new models has been the saturation of GPU…