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Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report Generation
Jinghan Sun, Dong Wei, Zhe Xu +7
Anatomical abnormality detection and report generation of chest X-ray (CXR) are two essential tasks in clinical practice. The former aims at localizing and characterizing cardiopul…
Dynamic Entity-Masked Graph Diffusion Model for histopathological image Representation Learning
Zhenfeng Zhuang, Min Cen, Yanfeng Li +4
Significant disparities between the features of natural images and those inherent to histopathological images make it challenging to directly apply and transfer pre-trained models…
SMILE-UHURA Challenge -- Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms
Soumick Chatterjee, Hendrik Mattern, Marc Dörner +45
The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesoscopic scale, represents a critical vulne…
GAInS: Gradient Anomaly-aware Biomedical Instance Segmentation
Runsheng Liu, Hao Jiang, Yanning Zhou +3
Instance segmentation plays a vital role in the morphological quantification of biomedical entities such as tissues and cells, enabling precise identification and delineation of di…
ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection
Junhao Lin, Lei Zhu, Jiaxing Shen +3
With the rapid development of depth sensor, more and more RGB-D videos could be obtained. Identifying the foreground in RGB-D videos is a fundamental and important task. However, t…
Cyclical Weight Consolidation: Towards Solving Catastrophic Forgetting in Serial Federated Learning
Haoyue Song, Jiacheng Wang, Liansheng Wang
Federated Learning (FL) has gained attention for addressing data scarcity and privacy concerns. While parallel FL algorithms like FedAvg exhibit remarkable performance, they face c…
Federated Modality-specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation
Qian Dai, Dong Wei, Hong Liu +3
Most existing federated learning (FL) methods for medical image analysis only considered intramodal heterogeneity, limiting their applicability to multimodal imaging applications.…
HistGen: Histopathology Report Generation via Local-Global Feature Encoding and Cross-modal Context Interaction
Zhengrui Guo, Jiabo Ma, Yingxue Xu +3
Histopathology serves as the gold standard in cancer diagnosis, with clinical reports being vital in interpreting and understanding this process, guiding cancer treatment and patie…
Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic Interaction
Hao Li, Ying Chen, Yifei Chen +5
Whole Slide Image (WSI) classification is often formulated as a Multiple Instance Learning (MIL) problem. Recently, Vision-Language Models (VLMs) have demonstrated remarkable perfo…
Less Could Be Better: Parameter-efficient Fine-tuning Advances Medical Vision Foundation Models
Chenyu Lian, Hong-Yu Zhou, Yizhou Yu +1
Parameter-efficient fine-tuning (PEFT) that was initially developed for exploiting pre-trained large language models has recently emerged as an effective approach to perform transf…