21 papers
Pathologist Attention-Aligned Report Generation for Prostate Histopathology
Ruoyu Xue, Suryakant Singh, Souradeep Chakraborty +12
The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracted from whole-slide images (W…
PathReportEval: A Systematic Benchmark for Pathology Report Generation
Suryakant Singh, Sejuti Majumder, Beatrice Knudsen +2
Pathology report generation from whole-slide images (WSIs) is a rapidly growing multimodal learning problem, yet progress is difficult to measure because existing studies use heter…
RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency
Wentao Huang, Meilong Xu, Xiaoling Hu +9
Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular heterogeneity and tissue organization.…
Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation
Suryakant Singh, Saarthak Kapse, Joel Saltz +1
Whole-slide images (WSIs) present a fundamental challenge for computational pathology due to their extreme resolution, multi-scale heterogeneity, and the requirement for clinically…
Gaze2Report: Radiology Report Generation via Visual-Gaze Prompt Tuning of LLMs
Aishik Konwer, Moinak Bhattacharya, Prateek Prasanna
Existing deep learning methods for radiology report generation enhance diagnostic efficiency but often overlook physician-informed medical priors. This leads to a suboptimal alignm…
Vessel-Aware Deep Learning for OCTA-Based Detection of AMD
Margalit G. Mitzner, Moinak Bhattacharya, Zhilin Zou +2
Age-related macular degeneration (AMD) is characterized by early micro-vascular alterations that can be captured non-invasively using optical coherence tomography angiography (OCTA…