CAPTIV8: A Comprehensive Large Scale Capsule Endoscopy Dataset For Integrated Diagnosis

Abstract

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Limited access to high-quality medical data poses a significant obstacle to automated diagnoses in medical modalities like Wireless Capsule Endoscopy (WCE), hindering potential advancements in automated medical diagnoses. This study presents a meticulously curated WCE dataset CAPTIV8, focused on the large colon and its pathologies, including Ulcerative Colitis (UC). Comprising a total of 1352 short video segments, totaling more than 200,000 frames with high mucosal visibility, the dataset features eight distinct types of pathology, along with signs of UC, accompanied by clinician-assigned text descriptions. To enhance its medical utility, the dataset integrates overlapping diagnoses from three diagnostic modalities: traditional and capsule endoscopy, and histology. Key attributes such as cleansing scores, text reports, capsule camera calibration and localization data have been incorporated to broaden its applicability in medical and artificial intelligence research. Designed for a wide spectrum of research challenges, from basic classification tasks to 3D reconstruction, CAPTIV8 aims to advance the incorporation of automated solutions in WCE diagnosis. The dataset can be accessed here:https:// dataverse.no/dataset.xhtml?persistentId=doi:10.18710/BSXNA1.