VIM-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein Expression

The dataset in this study includes 202 videos with a total of 422 minutes, reaching Kayseri City Hospital's gastroenterology department as colonoscopy videos and 1903 microscopy images between 2019 and 2021. It includes 399 colonoscopy, microscopy images, and pathological diagnoses of polyps, as well as immunohistochemical staining results for proteins that play an important role in the assessment of cancerous cells, such as staining results for p53 (clone: bp53-11), Ki-67 (clone: 30-9), CD34 (clone: QBend/10), PD-L1 (clone: SP142), BRAF (clone: V600E) and VEGF (clone: SP125). By sharing the data openly, we aim to facilitate benchmarking, exploratory analysis and transfer-learning studies on colorectal polyps and cancer. In combination with external datasets or pretrained models, the resource can help advance data-driven detection and characterisation work. The diverse range of polyps assigned to cancer stages from 201 patients makes this tool valuable for researchers and clinicians in furthering diagnosis and treatment.

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Publication Details

Journal
Scientific Data
Published
2025-12-03
DOI
https://doi.org/10.1038/s41597-025-06168-1
Primary Topic
Colorectal Cancer Screening and Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

VIM-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein Expression

Refika Sultan Doğan, Ebru Akay, Bülent Yılmaz, Serkan Doğan
Scientific Data
Colorectal Cancer Screening and Detection
article

VIM-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein Expression

Refika Sultan Doğan, Ebru Akay, Bülent Yılmaz, Serkan Doğan
article en

Abstract

The dataset in this study includes 202 videos with a total of 422 minutes, reaching Kayseri City Hospital's gastroenterology department as colonoscopy videos and 1903 microscopy images between 2019 and 2021. It includes 399 colonoscopy, microscopy images, and pathological diagnoses of polyps, as well as immunohistochemical staining results for proteins that play an important role in the assessment of cancerous cells, such as staining results for p53 (clone: bp53-11), Ki-67 (clone: 30-9), CD34 (clone: QBend/10), PD-L1 (clone: SP142), BRAF (clone: V600E) and VEGF (clone: SP125). By sharing the data openly, we aim to facilitate benchmarking, exploratory analysis and transfer-learning studies on colorectal polyps and cancer. In combination with external datasets or pretrained models, the resource can help advance data-driven detection and characterisation work. The diverse range of polyps assigned to cancer stages from 201 patients makes this tool valuable for researchers and clinicians in furthering diagnosis and treatment.

Scientific DataVol. 12(1)
Gulf University for Science & Technology (KW), Kayseri Eğitim ve Araştırma Hastanesi (TR), Abdullah Gül University (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 47%
Colorectal Cancer Screening and Detection
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