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28 papers
PathLang: A Language-Centered Benchmark for Vision-Language Models in Computational Pathology
Fanqi Cheng, Kuo Gong, Shangke Liu +15
Pathology vision-language models (VLMs) have shown strong visual perception ability, but their robustness in the language domain remains poorly characterized. Existing pathology VL…
Comprehensive Evaluation and Fine-Tuning of Foundational Cell Nuclei Segmentation Models in Renal Pathology
Ruijie Wu, Junlin Guo, Ruining Deng +4
Accurate nuclei instance segmentation is essential for quantitative renal pathology, yet general-purpose models often struggle with low contrast, dense nuclei, complex morphology,…
Benchmarking Active Spot Selection for Cost-Efficient Spatial Transcriptomics
Zheyu Zhu, Junchao Zhu, Fengbei Liu +7
Spatial transcriptomics (ST) measures gene expression in tissue context, but dense capture grids can be costly and may repeatedly sample morphologically similar regions. Most activ…
Seeing Abnormal from Normal: Glomerular Abnormality in Representations of Normal Renal Morphology
Greta Hasko, Rachit Saluja, Tianyu Shi +13
Fine-grained evaluation of glomerular pathology must distinguish normal glomeruli from abnormalities such as global and segmental glomerulosclerosis, obsolescent, ischemic, solidif…
SAGEAgent: A Self-Evolving Agent for Cost-Aware Modality Acquisition in Multimodal Survival Prediction
Chongyu Qu, Can Cui, Zhengyi Lu +8
Does every cancer patient truly need a complete diagnostic workup for accurate survival prediction? In multimodal clinical oncology, diagnostic modalities follow a clinically manda…
MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations
Leiyue Zhao, Tianyu Shi, Daniel Reisenbuchler +12
Instance-level quantification of kidney functional units is essential for morphometric analysis, yet most publicly available pathology datasets provide only semantic segmentation a…
An Interpretable Vision Transformer as a Fingerprint-Based Diagnostic Aid for Kabuki and Wiedemann-Steiner Syndromes
Marilyn Lionts, Arnhildur Tomasdottir, Viktor I. Agustsson +3
Kabuki syndrome (KS) and Wiedemann-Steiner syndrome (WSS) are rare but distinct developmental disorders that share overlapping clinical features, including neurodevelopmental delay…
Explainable Pathomics Feature Visualization via Correlation-aware Conditional Feature Editing
Yuechen Yang, Junlin Guo, Ruining Deng +9
Pathomics is a recent approach that offers rich quantitative features beyond what black-box deep learning can provide, supporting more reproducible and explainable biomarkers in di…
SCR2-ST: Combine Single Cell with Spatial Transcriptomics for Efficient Active Sampling via Reinforcement Learning
Junchao Zhu, Ruining Deng, Junlin Guo +13
Spatial transcriptomics (ST) is an emerging technology that enables researchers to investigate the molecular relationships underlying tissue morphology. However, acquiring ST data…
HistoWAS: A Pathomics Framework for Large-Scale Feature-Wide Association Studies of Tissue Topology and Patient Outcomes
Yuechen Yang, Junlin Guo, Yanfan Zhu +10
High-throughput "pathomic" analysis of Whole Slide Images (WSIs) offers new opportunities to study tissue characteristics and for biomarker discovery. However, the clinical relevan…
How Close Are We? Limitations and Progress of AI Models in Banff Lesion Scoring
Yanfan Zhu, Juming Xiong, Ruining Deng +7
The Banff Classification provides the global standard for evaluating renal transplant biopsies, yet its semi-quantitative nature, complex criteria, and inter-observer variability p…
Evaluating New AI Cell Foundation Models on Challenging Kidney Pathology Cases Unaddressed by Previous Foundation Models
Runchen Wang, Junlin Guo, Siqi Lu +12
Accurate cell nuclei segmentation is critical for downstream tasks in kidney pathology and remains a major challenge due to the morphological diversity and imaging variability of r…
Organoid Tracker: A SAM2-Powered Platform for Zero-shot Cyst Analysis in Human Kidney Organoid Videos
Xiaoyu Huang, Lauren M Maxson, Trang Nguyen +2
Recent advances in organoid models have revolutionized the study of human kidney disease mechanisms and drug discovery by enabling scalable, cost-effective research without the nee…
MedFoundationHub: A Lightweight and Secure Toolkit for Deploying Medical Vision Language Foundation Models
Xiao Li, Yanfan Zhu, Ruining Deng +6
Recent advances in medical vision-language models (VLMs) open up remarkable opportunities for clinical applications such as automated report generation, copilots for physicians, an…
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…
Img2ST-Net: Efficient High-Resolution Spatial Omics Prediction from Whole Slide Histology Images via Fully Convolutional Image-to-Image Learning
Junchao Zhu, Ruining Deng, Junlin Guo +10
Recent advances in multi-modal AI have demonstrated promising potential for generating the currently expensive spatial transcriptomics (ST) data directly from routine histology ima…
ZeroReg3D: A Zero-shot Registration Pipeline for 3D Consecutive Histopathology Image Reconstruction
Juming Xiong, Ruining Deng, Jialin Yue +10
Histological analysis plays a crucial role in understanding tissue structure and pathology. While recent advancements in registration methods have improved 2D histological analysis…
IRS: Incremental Relationship-guided Segmentation for Digital Pathology
Ruining Deng, Junchao Zhu, Juming Xiong +14
Continual learning is rapidly emerging as a key focus in computer vision, aiming to develop AI systems capable of continuous improvement, thereby enhancing their value and practica…
CASC-AI: Consensus-aware Self-corrective Learning for Noise Cell Segmentation
Ruining Deng, Yihe Yang, David J. Pisapia +15
Multi-class cell segmentation in high-resolution gigapixel whole slide images (WSIs) is crucial for various clinical applications. However, training such models typically requires…
MagNet: Multi-Level Attention Graph Network for Predicting High-Resolution Spatial Transcriptomics
Junchao Zhu, Ruining Deng, Tianyuan Yao +12
The rapid development of spatial transcriptomics (ST) offers new opportunities to explore the gene expression patterns within the spatial microenvironment. Current research integra…
KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level
Ruining Deng, Tianyuan Yao, Yucheng Tang +44
Chronic kidney disease (CKD) is a major global health issue, affecting over 10% of the population and causing significant mortality. While kidney biopsy remains the gold standard f…
Towards Fine-grained Renal Vasculature Segmentation: Full-Scale Hierarchical Learning with FH-Seg
Yitian Long, Zhongze Wu, Xiu Su +4
Accurate fine-grained segmentation of the renal vasculature is critical for nephrological analysis, yet it faces challenges due to diverse and insufficiently annotated images. Exis…
PySpatial: A High-Speed Whole Slide Image Pathomics Toolkit
Yuechen Yang, Yu Wang, Tianyuan Yao +5
Whole Slide Image (WSI) analysis plays a crucial role in modern digital pathology, enabling large-scale feature extraction from tissue samples. However, traditional feature extract…
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…