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VIM-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein Expression
Refika Sultan Doğan1,2, Ebru Akay3, Serkan Doğan4
1Department of Bioengineering, Faculty of Life and Natural Sciences, Abdullah Gül University, Kayseri, 38080, Türkiye. refikasultan.dogan@agu.edu.tr.
Scientific Data
|December 3, 2025
Summary
This study introduces a comprehensive dataset of colonoscopy videos and microscopy images for colorectal polyps and cancer research. The openly shared data aims to advance diagnostic and characterization tools for researchers and clinicians.
Area of Science:
- Gastroenterology
- Oncology
- Medical Imaging
- Pathology
Background:
- Colorectal polyps and cancer diagnosis relies on accurate interpretation of colonoscopy and pathology data.
- Limited availability of diverse, annotated datasets hinders the development of advanced diagnostic tools.
Purpose of the Study:
- To create and share a multimodal dataset of colonoscopy videos, microscopy images, and pathological diagnoses for colorectal polyps.
- To facilitate benchmarking, exploratory analysis, and transfer-learning studies in colorectal cancer research.
Main Methods:
- Collected 202 colonoscopy videos (422 minutes) and 1903 microscopy images from 2019-2021.
- Included pathological diagnoses, immunohistochemical staining results for key proteins (p53, Ki-67, CD34, PD-L1, BRAF, VEGF).
Main Results:
- A dataset comprising 399 colonoscopy images, microscopy images, and associated diagnostic data.
- Detailed immunohistochemical staining results for proteins crucial in cancer cell assessment.
Conclusions:
- The dataset provides a valuable resource for advancing data-driven detection and characterization of colorectal polyps and cancer.
- Open data sharing will accelerate research in diagnosis and treatment strategies for colorectal conditions.
