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20232026
most citedDeep Learning-Based Open Source Toolkit for Eosinophil Detection in Pediatric Eosinophilic Esophagitis

1 citations · 4 across the 34 of their papers we have counts for

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Showing 2024Show all

10 papers · 1 filter

cs.CV2024★ 1 cited

ASIGN: An Anatomy-aware Spatial Imputation Graphic Network for 3D Spatial Transcriptomics

Junchao Zhu, Ruining Deng, Tianyuan Yao +9

Spatial transcriptomics (ST) is an emerging technology that enables medical computer vision scientists to automatically interpret the molecular profiles underlying morphological fe…

eess.IV2024

Cross-organ Deployment of EOS Detection AI without Retraining: Feasibility and Limitation

Yifei Wu, Juming Xiong, Tianyuan Yao +5

Chronic rhinosinusitis (CRS) is characterized by persistent inflammation in the paranasal sinuses, leading to typical symptoms of nasal congestion, facial pressure, olfactory dysfu…

cs.CV2024

GloFinder: AI-empowered QuPath Plugin for WSI-level Glomerular Detection, Visualization, and Curation

Jialin Yue, Tianyuan Yao, Ruining Deng +7

Artificial intelligence (AI) has demonstrated significant success in automating the detection of glomeruli, the key functional units of the kidney, from whole slide images (WSIs) i…

cs.CV2024★ 1 cited

Evaluating Cell AI Foundation Models in Kidney Pathology with Human-in-the-Loop Enrichment

Junlin Guo, Siqi Lu, Can Cui +14

Training AI foundation models has emerged as a promising large-scale learning approach for addressing real-world healthcare challenges, including digital pathology. While many of t…

cs.CV2024

Automatic Image Unfolding and Stitching Framework for Esophageal Lining Video Based on Density-Weighted Feature Matching

Muyang Li, Juming Xiong, Ruining Deng +4

Endoscopy is a crucial tool for diagnosing the gastrointestinal tract, but its effectiveness is often limited by a narrow field of view and the dynamic nature of the internal envir…

eess.IV2024

Assessment of Cell Nuclei AI Foundation Models in Kidney Pathology

Junlin Guo, Siqi Lu, Can Cui +14

Cell nuclei instance segmentation is a crucial task in digital kidney pathology. Traditional automatic segmentation methods often lack generalizability when applied to unseen datas…

eess.IV2024

HATs: Hierarchical Adaptive Taxonomy Segmentation for Panoramic Pathology Image Analysis

Ruining Deng, Quan Liu, Can Cui +10

Panoramic image segmentation in computational pathology presents a remarkable challenge due to the morphologically complex and variably scaled anatomy. For instance, the intricate…

cs.CV2024

Weighted Circle Fusion: Ensembling Circle Representation from Different Object Detection Results

Jialin Yue, Tianyuan Yao, Ruining Deng +5

Recently, the use of circle representation has emerged as a method to improve the identification of spherical objects (such as glomeruli, cells, and nuclei) in medical imaging stud…

eess.IV2024★ 1 cited

PrPSeg: Universal Proposition Learning for Panoramic Renal Pathology Segmentation

Ruining Deng, Quan Liu, Can Cui +11

Understanding the anatomy of renal pathology is crucial for advancing disease diagnostics, treatment evaluation, and clinical research. The complex kidney system comprises various…

cs.CV2024

Circle Representation for Medical Instance Object Segmentation

Juming Xiong, Ethan H. Nguyen, Yilin Liu +8

Recently, circle representation has been introduced for medical imaging, designed specifically to enhance the detection of instance objects that are spherically shaped (e.g., cells…