4 citations · 8 across the 23 of their papers we have counts for
12 papers · 1 filter
DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction
Junchao Zhu, Ruining Deng, Junlin Guo +11
Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing methods reduce this task to…
From Classification to Cross-Modal Understanding: Leveraging Vision-Language Models for Fine-Grained Renal Pathology
Zhenhao Guo, Rachit Saluja, Tianyuan Yao +14
Fine-grained glomerular subtyping is essential for kidney biopsy interpretation, yet it presents a harder setting than the broad organ- or disease-level recognition tasks commonly…
Glo-VLMs: Leveraging Vision-Language Models for Fine-Grained Diseased Glomerulus Classification
Zhenhao Guo, Rachit Saluja, Tianyuan Yao +8
Vision-language models (VLMs) have shown considerable potential in digital pathology, yet their effectiveness remains limited for fine-grained, disease-specific classification task…
DyMorph-B2I: Dynamic and Morphology-Guided Binary-to-Instance Segmentation for Renal Pathology
Leiyue Zhao, Yuechen Yang, Yanfan Zhu +7
Accurate morphological quantification of renal pathology functional units relies on instance-level segmentation, yet most existing datasets and automated methods provide only binar…
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…
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…
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…
PFPs: Prompt-guided Flexible Pathological Segmentation for Diverse Potential Outcomes Using Large Vision and Language Models
Can Cui, Ruining Deng, Junlin Guo +4
The Vision Foundation Model has recently gained attention in medical image analysis. Its zero-shot learning capabilities accelerate AI deployment and enhance the generalizability o…
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…
mTREE: Multi-Level Text-Guided Representation End-to-End Learning for Whole Slide Image Analysis
Quan Liu, Ruining Deng, Can Cui +4
Multi-modal learning adeptly integrates visual and textual data, but its application to histopathology image and text analysis remains challenging, particularly with large, high-re…
ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers
Quan Liu, Brandon T. Swartz, Ivan Kravchenko +2
Deep neural networks (DNNs) have heavily relied on traditional computational units like CPUs and GPUs. However, this conventional approach brings significant computational burdens,…
Fusion: Bayesian-based Multimodal Multi-level Fusion on Colorectal Cancer Microsatellite Instability Prediction
Quan Liu, Jiawen Yao, Lisha Yao +6
Colorectal cancer (CRC) micro-satellite instability (MSI) prediction on histopathology images is a challenging weakly supervised learning task that involves multi-instance learning…