activity
20212023
most citedSegment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

97 citations · 107 across the 6 of their papers we have counts for

collaborators

6 papers

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…

eess.IV2023★ 97 cited

Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

Ruining Deng, Can Cui, Quan Liu +13

The segment anything model (SAM) was released as a foundation model for image segmentation. The promptable segmentation model was trained by over 1 billion masks on 11M licensed an…

cs.CV2022

Cross-scale Attention Guided Multi-instance Learning for Crohn's Disease Diagnosis with Pathological Images

Ruining Deng, Can Cui, Lucas W. Remedios +12

Multi-instance learning (MIL) is widely used in the computer-aided interpretation of pathological Whole Slide Images (WSIs) to solve the lack of pixel-wise or patch-wise annotation…

cs.LG2022★ 9 cited

Deep Multi-modal Fusion of Image and Non-image Data in Disease Diagnosis and Prognosis: A Review

Can Cui, Haichun Yang, Yaohong Wang +6

The rapid development of diagnostic technologies in healthcare is leading to higher requirements for physicians to handle and integrate the heterogeneous, yet complementary data th…

eess.IV2021★ 1 cited

Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging

Shunxing Bao, Yucheng Tang, Ho Hin Lee +8

Multiplex immunofluorescence (MxIF) is an emerging imaging technique that produces the high sensitivity and specificity of single-cell mapping. With a tenet of 'seeing is believing…