1 citations · 1 across the 9 of their papers we have counts for
10 papers
Self-Supervised Learning for Knee Osteoarthritis: Diagnostic Limitations and Prognostic Value of Hospital Data
Haresh Rengaraj Rajamohan, Yuxuan Chen, Kyunghyun Cho +1
This study assesses whether self-supervised learning (SSL) improves knee osteoarthritis (OA) modeling for diagnosis and prognosis relative to ImageNet-pretrained initialization. We…
StainNet: Scaling Self-Supervised Foundation Models on Immunohistochemistry and Special Stains for Computational Pathology
Jiawen Li, Jiali Hu, Xitong Ling +6
Foundation models trained with self-supervised learning (SSL) on large-scale histological images have significantly accelerated the development of computational pathology. These mo…
Deformable Attention Graph Representation Learning for Histopathology Whole Slide Image Analysis
Mingxi Fu, Xitong Ling, Yuxuan Chen +6
Accurate classification of Whole Slide Images (WSIs) and Regions of Interest (ROIs) is a fundamental challenge in computational pathology. While mainstream approaches often adopt M…
An Inclusive Foundation Model for Generalizable Cytogenetics in Precision Oncology
Changchun Yang, Weiqian Dai, Yilan Zhang +8
Chromosome analysis is vital for diagnosing genetic disorders and guiding cancer therapy decisions through the identification of somatic clonal aberrations. However, developing an…
Cross-Modal Prototype Allocation: Unsupervised Slide Representation Learning via Patch-Text Contrast in Computational Pathology
Yuxuan Chen, Jiawen Li, Jiali Hu +4
With the rapid advancement of pathology foundation models (FMs), the representation learning of whole slide images (WSIs) attracts increasing attention. Existing studies develop hi…
Multimodal Distillation-Driven Ensemble Learning for Long-Tailed Histopathology Whole Slide Images Analysis
Xitong Ling, Yifeng Ping, Jiawen Li +8
Multiple Instance Learning (MIL) plays a significant role in computational pathology, enabling weakly supervised analysis of Whole Slide Image (WSI) datasets. The field of WSI anal…
Dynamic Hypergraph Representation for Bone Metastasis Cancer Analysis
Yuxuan Chen, Jiawen Li, Huijuan Shi +5
Bone metastasis analysis is a significant challenge in pathology and plays a critical role in determining patient quality of life and treatment strategies. The microenvironment and…
BURExtract-Llama: An LLM for Clinical Concept Extraction in Breast Ultrasound Reports
Yuxuan Chen, Haoyan Yang, Hengkai Pan +6
Breast ultrasound is essential for detecting and diagnosing abnormalities, with radiology reports summarizing key findings like lesion characteristics and malignancy assessments. E…
RetMIL: Retentive Multiple Instance Learning for Histopathological Whole Slide Image Classification
Hongbo Chu, Qiehe Sun, Jiawen Li +5
Histopathological whole slide image (WSI) analysis with deep learning has become a research focus in computational pathology. The current paradigm is mainly based on multiple insta…
Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image Analysis
Jiawen Li, Yuxuan Chen, Hongbo Chu +4
Histopathological whole slide images (WSIs) classification has become a foundation task in medical microscopic imaging processing. Prevailing approaches involve learning WSIs as in…