28 citations · 53 across the 7 of their papers we have counts for
7 papers
SlideBank: A Persistent Hierarchical Evidence Bank for Consistent Whole-Slide Reasoning
Beidi Zhao, Gexin Huang, Ciro Zhang +6
Whole-slide images (WSIs) are challenging for vision-language reasoning because diagnostically relevant morphology is sparse, heterogeneous, and distributed across gigapixel-scale…
UltraVR: A Diagnostic Ultra-Resolution Image-VQA Benchmark for Evidence-Grounded Reasoning
Gexin Huang, Yanting Yang, Myeongkyun Kang +6
Vision-language models (VLMs) excel on visual question answering and multimodal reasoning benchmarks. Yet their capability on ultra-resolution images - where critical evidence is t…
Plug-and-Play Logit Fusion for Heterogeneous Pathology Foundation Models
Gexin Huang, Anqi Li, Yusheng Tan +4
Pathology foundation models (FMs) have become central to computational histopathology, offering strong transfer performance across a wide range of diagnostic and prognostic tasks.…
PTCMIL: Multiple Instance Learning via Prompt Token Clustering for Whole Slide Image Analysis
Beidi Zhao, SangMook Kim, Hao Chen +4
Multiple Instance Learning (MIL) has advanced WSI analysis but struggles with the complexity and heterogeneity of WSIs. Existing MIL methods face challenges in aggregating diverse…
LESS: Label-efficient Multi-scale Learning for Cytological Whole Slide Image Screening
Beidi Zhao, Wenlong Deng, Zi Han +5
In computational pathology, multiple instance learning (MIL) is widely used to circumvent the computational impasse in giga-pixel whole slide image (WSI) analysis. It usually consi…
Machine Intelligence-Driven Classification of Cancer Patients-Derived Extracellular Vesicles using Fluorescence Correlation Spectroscopy: Results from a Pilot Study
Abicumaran Uthamacumaran, Mohamed Abdouh, Kinshuk Sengupta +5
Patient-derived extracellular vesicles (EVs) that contains a complex biological cargo is a valuable source of liquid biopsy diagnostics to aid in early detection, cancer screening,…
Machine Learning Characterization of Cancer Patients-Derived Extracellular Vesicles using Vibrational Spectroscopies
Abicumaran Uthamacumaran, Samir Elouatik, Mohamed Abdouh +3
The early detection of cancer is a challenging problem in medicine. The blood sera of cancer patients are enriched with heterogeneous secretory lipid bound extracellular vesicles (…