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CC BY-NC-ND 4.0 · Endosc Int Open 2017; 05(06): E477-E483
DOI: 10.1055/s-0043-105488
Original article
Eigentümer und Copyright ©Georg Thieme Verlag KG 2017

KID Project: an internet-based digital video atlas of capsule endoscopy for research purposes

Anastasios Koulaouzidis
1   Centre for Liver and Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UK
,
Dimitris K. Iakovidis
2   University of Thessaly, Department of Computer Science and Biomedical Informatics, Volos, Thessaly, Greece
,
Diana E. Yung
1   Centre for Liver and Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UK
,
Emanuele Rondonotti
3   Gastroenterology Unit, Valduce Hospital, Como, Italy
,
Uri Kopylov
4   Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, and Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel
,
John N. Plevris
1   Centre for Liver and Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UK
,
Ervin Toth
5   Department of Gastroenterology, Skåne University Hospital, Lund University, Malmö, Sweden
,
Abraham Eliakim   *
4   Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, and Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel
,
Gabrielle Wurm Johansson   *
5   Department of Gastroenterology, Skåne University Hospital, Lund University, Malmö, Sweden
,
Wojciech Marlicz   *
6   Department of Gastroenterology, Pomeranian Medical University, Szezecin, Poland
,
Georgios Mavrogenis   *
7   Gastroenterology and Endoscopy Center of Mytilene, Mytilene, Lesvos, Greece
,
Artur Nemeth   *
5   Department of Gastroenterology, Skåne University Hospital, Lund University, Malmö, Sweden
,
Henrik Thorlacius   *
8   Department of Clinical Sciences, Lund University, Malmö, Sweden
,
Gian Eugenio Tontini   *
9   Gastroenterology and Digestive Endoscopy Unit, IRCCS Policlinico San Donato, Milan, Italy
› Author Affiliations
Further Information

Publication History

submitted 07 September 2016

accepted after revision 06 February 2017

Publication Date:
31 May 2017 (online)

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Abstract

Background and aims Capsule endoscopy (CE) has revolutionized small-bowel (SB) investigation. Computational methods can enhance diagnostic yield (DY); however, incorporating machine learning algorithms (MLAs) into CE reading is difficult as large amounts of image annotations are required for training. Current databases lack graphic annotations of pathologies and cannot be used. A novel database, KID, aims to provide a reference for research and development of medical decision support systems (MDSS) for CE.

Methods Open-source software was used for the KID database. Clinicians contribute anonymized, annotated CE images and videos. Graphic annotations are supported by an open-access annotation tool (Ratsnake). We detail an experiment based on the KID database, examining differences in SB lesion measurement between human readers and a MLA. The Jaccard Index (JI) was used to evaluate similarity between annotations by the MLA and human readers.

Results The MLA performed best in measuring lymphangiectasias with a JI of 81 ± 6 %. The other lesion types were: angioectasias (JI 64 ± 11 %), aphthae (JI 64 ± 8 %), chylous cysts (JI 70 ± 14 %), polypoid lesions (JI 75 ± 21 %), and ulcers (JI 56 ± 9 %).

Conclusion MLA can perform as well as human readers in the measurement of SB angioectasias in white light (WL). Automated lesion measurement is therefore feasible. KID is currently the only open-source CE database developed specifically to aid development of MDSS. Our experiment demonstrates this potential.

* KID working group


 

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