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Mehmet Saygin Seyfioglu

4 accepted papers

2025

MedicalNarratives: Connecting Medical Vision and Language with Localized Narratives

NeurIPS 2025poster

Multi-modal models are data hungry. While datasets with natural images are abundant, medical image datasets can not afford the same luxury. To enable representation learning for medical images at scale, we turn to YouTube, a platform with a large reservoir of open-source medical pedagogical videos.…

Cited by 0SourceScholar
2025

PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology

ICCV 2025poster

Diagnosing diseases through histopathology whole slide images (WSIs) is fundamental in modern pathology but is challenged by the gigapixel scale and complexity of WSIs. Trained histopathologists overcome this challenge by navigating the WSI, looking for relevant patches, taking notes, and compiling…

Cited by 0SourcePDFScholar
2024

Quilt-LLaVA: Visual Instruction Tuning by Extracting Localized Narratives from Open-Source Histopathology Videos

CVPR 2024poster

Diagnosis in histopathology requires a global whole slide images (WSIs) analysis requiring pathologists to compound evidence from different WSI patches. The gigapixel scale of WSIs poses a challenge for histopathology multi-modal models. Training multi-model models for histopathology requires instru…

Cited by 34SourcePDFScholar
2023

Quilt-1M: One Million Image-Text Pairs for Histopathology

NeurIPS 2023oral

Recent accelerations in multi-modal applications have been made possible with the plethora of image and text data available online. However, the scarcity of analogous data in the medical field, specifically in histopathology, has slowed comparable progress. To enable similar representation learning…