8 papers
Paired Uterine Whole-Slide Images and Pathology Reports for Multimodal Computational Pathology
Han Li, Jingsong Liu, Ayako Ura +14
Uterine diseases represent an important category of gynecologic pathology and require accurate histopathological assessment for diagnosis and treatment planning. Whole-slide images…
Clinical Priors Guided Lung Disease Detection in 3D CT Scans
Kejin Lu, Jianfa Bai, Qingqiu Li +5
Accurate classification of lung diseases from chest CT scans plays an important role in computer-aided diagnosis systems. However, medical imaging datasets often suffer from severe…
Vision-Language Model Based Multi-Expert Fusion for CT Image Classification
Jianfa Bai, Kejin Lu, Runtian Yuan +5
Robust detection of COVID-19 from chest CT remains challenging in multi-institutional settings due to substantial source shift, source imbalance, and hidden test-source identities.…
A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model
Zhe Xu, Ziyi Liu, Junlin Hou +13
Multimodal large language models (MLLMs) have emerged as powerful tools for computational pathology, offering unprecedented opportunities to integrate pathological images with lang…
Advancing Lung Disease Diagnosis in 3D CT Scans
Qingqiu Li, Runtian Yuan, Junlin Hou +4
To enable more accurate diagnosis of lung disease in chest CT scans, we propose a straightforward yet effective model. Firstly, we analyze the characteristics of 3D CT scans and re…
Multi-Source COVID-19 Detection via Variance Risk Extrapolation
Runtian Yuan, Qingqiu Li, Junlin Hou +4
We present our solution for the Multi-Source COVID-19 Detection Challenge, which aims to classify chest CT scans into COVID and Non-COVID categories across data collected from four…