activity
20222025
most citedFDVTS's Solution for 2nd COV19D Competition on COVID-19 Detection and Severity Analysis

4 citations · 7 across the 6 of their papers we have counts for

collaborators
Showing eess.IVShow all

7 papers · 1 filter

eess.IV2025

Solutions for Mitotic Figure Detection and Atypical Classification in MIDOG 2025

Shuting Xu, Runtong Liu, Zhixuan Chen +2

Deep learning has driven significant advances in mitotic figure analysis within computational pathology. In this paper, we present our approach to the Mitosis Domain Generalization…

eess.IV2025

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…

eess.IV2025

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…

eess.IV2024

Advancing COVID-19 Detection in 3D CT Scans

Qingqiu Li, Runtian Yuan, Junlin Hou +4

To make a more accurate diagnosis of COVID-19, we propose a straightforward yet effective model. Firstly, we analyse the characteristics of 3D CT scans and remove the non-lung part…

eess.IV2024

Domain Adaptation Using Pseudo Labels for COVID-19 Detection

Runtian Yuan, Qingqiu Li, Junlin Hou +4

In response to the need for rapid and accurate COVID-19 diagnosis during the global pandemic, we present a two-stage framework that leverages pseudo labels for domain adaptation to…

eess.IV20232 cited

DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images

Bo Qian, Hao Chen, Xiangning Wang +18

Computer-assisted automatic analysis of diabetic retinopathy (DR) is of great importance in reducing the risks of vision loss and even blindness. Ultra-wide optical coherence tomog…