AI-KODA Dataset: An AI-Image Dataset for Automatic Assessment of Cleanliness in Video Capsule Endoscopy as per Korea-Canada Scores

AI-Image Dataset for Automatic Assessment of Cleanliness in Video Capsule Endoscopy as per KODA scores
Artificial Intelligence-Korea Canada (AI-KODA) dataset is a medically annotated, multi-label image AI dataset collected from Department of Gastroenterology and HNU, All India Institute of Medical Sciences, New Delhi. It consists of 2173 video capsule endoscopy frames with KODA score labels.
There are three folders in the dataset namely:
ImagesLabelsSample python files with no augmentationThe Images folder contains 2173 Video Capsule Endoscopy frames of 28 patients. 1539 frames are sequential in nature and were obtained after every 5 minutes from the 28 patient videos. 634 frames are non-sequential in nature and were obtained randomly from the 28 patient videos. F minutes in the image path represents five-minute frames. DF in the image path represents default frames. The images are of 320 x 320 resolution.
The labels folder contains two types of files in excel and CSV format. One is multi-hot encoded in zeros and ones format. Another one contains the exact labels. Sample python files are attached for its use. Please note that no augmentation has been performed. Users may augment themselves as per case use. Further information will be shared upon acceptance of the manuscript(s) in consideration.
Authors are thankful to Dr. Mohammad Tabish, Dr. Rajat Bansal and Dr. Syed Ahmed from Department of Gastroenterology & HNU, All India Institute of Medical Sciences, New Delhi for helping in annotation of the dataset. Thanks to Nikita Garg for helping in the development of the AI-KODA application. The authors also acknowledge the support of SERB, a statutory body of the Department of Science and Technology, Government of India for funding this research work under the Core Research Grant (CRG/2022/001755).