6 papers · 1 filter
Chart-FR1: Visual Focus-Driven Fine-Grained Reasoning on Dense Charts
Hongkun Pan, Yuwei Wu, Wanyi Hong +8
Multimodal large language models (MLLMs) have shown considerable potential in chart understanding and reasoning tasks. However, they still struggle with high information density (H…
Dino-NestedUNet: Unlocking Foundation Vision Encoders for Pathology Tumor Bulk Segmentation via Dense Decoding
Tianyang Wang, Ziyu Su, Abdul Rehman Akbar +7
Vision foundation models (VFMs), such as DINOv3, provide rich semantic representations that are promising for computational pathology. However, many current adaptations pair frozen…
Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localization
Tianyang Wang, Ziyu Su, Abdul Rehman Akbar +6
The expanding ecosystem of pathology foundation models has produced powerful but fragmented tile-level representations, limiting their use in clinical tasks that require unified sl…
Learning the Language of Histopathology Images reveals Prognostic Subgroups in Invasive Lung Adenocarcinoma Patients
Abdul Rehman Akbar, Usama Sajjad, Ziyu Su +5
Recurrence remains a major clinical challenge in surgically resected invasive lung adenocarcinoma, where existing grading and staging systems fail to capture the cellular complexit…
Progressive Translation of H&E to IHC with Enhanced Structural Fidelity
Yuhang Kang, Ziyu Su, Tianyang Wang +3
Compared to hematoxylin-eosin (H&E) staining, immunohistochemistry (IHC) not only maintains the structural features of tissue samples, but also provides high-resolution protein loc…
Morphology-Aware Prognostic model for Five-Year Survival Prediction in Colorectal Cancer from H&E Whole Slide Images
Usama Sajjad, Abdul Rehman Akbar, Ziyu Su +5
Colorectal cancer (CRC) remains the third most prevalent malignancy globally, with approximately 154,000 new cases and 54,000 projected deaths anticipated for 2025. The recent adva…