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

Anastasios Koulaouzidis; Dimitris K. Iakovidis; Diana E. Yung; Emanuele Rondonotti; Uri Kopylov; John N. Plevris; Ervin Toth; Abraham Eliakim; Gabrielle Wurm Johansson; Wojciech Marlicz; Georgios Mavrogenis; Artur Nemeth; Henrik Thorlacius; Gian Eugenio Tontini

doi:10.1055/s-0043-105488

Endoscopy International Open, Inhaltsverzeichnis

CC BY-NC-ND 4.0 · Endosc Int Open 2017; 05(06): E477-E483
DOI: 10.1055/s-0043-105488

Original article

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

Anastasios Koulaouzidis

¹Centre for Liver and Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UK

,

Dimitris K. Iakovidis

²University of Thessaly, Department of Computer Science and Biomedical Informatics, Volos, Thessaly, Greece

,

Diana E. Yung

¹Centre for Liver and Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UK

,

Emanuele Rondonotti

³Gastroenterology Unit, Valduce Hospital, Como, Italy

,

Uri Kopylov

⁴Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, and Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel

,

John N. Plevris

¹Centre for Liver and Digestive Disorders, The Royal Infirmary of Edinburgh, Edinburgh, UK

,

Ervin Toth

⁵Department of Gastroenterology, Skåne University Hospital, Lund University, Malmö, Sweden

,

Abraham Eliakim^*

⁴Department of Gastroenterology, Sheba Medical Center, Tel Hashomer, and Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel

,

Gabrielle Wurm Johansson^*

⁵Department of Gastroenterology, Skåne University Hospital, Lund University, Malmö, Sweden

,

Wojciech Marlicz^*

⁶Department of Gastroenterology, Pomeranian Medical University, Szezecin, Poland

,

Georgios Mavrogenis^*

⁷Gastroenterology and Endoscopy Center of Mytilene, Mytilene, Lesvos, Greece

,

Artur Nemeth^*

⁵Department of Gastroenterology, Skåne University Hospital, Lund University, Malmö, Sweden

,

Henrik Thorlacius^*

⁸Department of Clinical Sciences, Lund University, Malmö, Sweden

,

Gian Eugenio Tontini^*

⁹Gastroenterology and Digestive Endoscopy Unit, IRCCS Policlinico San Donato, Milan, Italy

› Institutsangaben

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.

Volltext

Referenzen

References
1 Koulaouzidis A, Rondonotti E, Karargyris A. Small-bowel capsule endoscopy: A ten-point contemporary review. World J Gastroenterol 2013; 19: 3726-3746
2 Hale M, McAlindon ME. Capsule endoscopy as a panenteric diagnostic tool. Br J Surg 2014; 101: 148-149
3 Iakovidis DK, Koulaouzidis A. Software for enhanced video capsule endoscopy: challenges for essential progress. Nat Rev Gastroenterol Hepatol 2015; 12: 172-186
4 Zheng Y, Hawkins L, Wolff J. et al. Detection of lesions during capsule endoscopy: physician performance is disappointing. Am J Gastroenterol 2012; 107: 554-560
5 Selected websites recommended by the Atlas of Gastrointestinal Endoscopy. Available at: http://www.endoatlas.com/websites.html
6 Cong Y, Wang S, Liu J. et al. Deep sparse feature selection for computer aided endoscopy diagnosis. Pattern Recognit 2015; 48: 907-917
7 Korman LY, Delvaux M, Gay G. et al. Capsule Endoscopy Structured Terminology (CEST): Proposal of a standardized and structured terminology for reporting capsule endoscopy procedures. Endoscopy 2005; 37: 951-959
8 Iakovidis DK, Goudas T, Smailis C. et al. Ratsnake: A versatile image annotation tool with application to computer-aided diagnosis. Sci World J 2014; 286856
9 Freitas F, Schulz S, Moraes E. Survey of current terminologies and ontologies in biology and medicine. RECIIS Electron J Commun Inf Innov Health 2009; 3: 7-18
10 Lankton S, Tannenbaum A. Localizing region-based active contours. IEEE Trans Image Process 2008; 17: 2029-2039
11 Iakovidis DK, Koulaouzidis A. Automatic lesion detection in capsule endoscopy based on color saliency: Closer to an essential adjunct for reviewing software. Gastrointest Endosc 2014; 80: 877-883
12 Pont-Tuset J, Marques F. Supervised evaluation of image segmentation and object proposal techniques. IEEE Trans Pattern Anal Mach Intell 2016; 38: 1465-1478
13 Kilbridge PM, Classen DC, Kohn L. et al. The informatics opportunities at the intersection of patient safety and clinical informatics. J Am Med Inform Assoc 2008; 15: 397-407
14 Van der Sommen F, Zinger S, Curvers WL. et al. Computer-aided detection of early neoplastic lesions in Barrett’s esophagus. Endoscopy 2016; 48: 617-624
15 Koulaouzidis A, Yung D, Rondonotti E. et al. Chromoendoscopy for angiectasias in capsule endoscopy; blue or just white?. Gut 2016; 65: A52-A53