Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study
This paper presents an active locomotion capsule endoscope system with 5D position sensing and real-time automated polyp detection for small-bowel and colon applications. An electromagnetic actuation system (EMA) consisting of stationary electromagnets is utilized to remotely control a magnetic caps...
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| Materiálatiipa: | Artihkal |
| Giella: | English |
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MDPI AG
2021-10-01
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| Ráidu: | Diagnostics |
| Fáttát: | |
| Liŋkkat: | https://www.mdpi.com/2075-4418/11/10/1878 |
| _version_ | 1827679765609316352 |
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| author | Manh Cuong Hoang Kim Tien Nguyen Jayoung Kim Jong-Oh Park Chang-Sei Kim |
| author_facet | Manh Cuong Hoang Kim Tien Nguyen Jayoung Kim Jong-Oh Park Chang-Sei Kim |
| author_sort | Manh Cuong Hoang |
| collection | DOAJ |
| description | This paper presents an active locomotion capsule endoscope system with 5D position sensing and real-time automated polyp detection for small-bowel and colon applications. An electromagnetic actuation system (EMA) consisting of stationary electromagnets is utilized to remotely control a magnetic capsule endoscope with multi-degree-of-freedom locomotion. For position sensing, an electronic system using a magnetic sensor array is built to track the position and orientation of the magnetic capsule during movement. The system is integrated with a deep learning model, named YOLOv3, which can automatically identify colorectal polyps in real-time with an average precision of 85%. The feasibility of the proposed method concerning active locomotion and localization is validated and demonstrated through in vitro experiments in a phantom duodenum. This study provides a high-potential solution for automatic diagnostics of the bowel and colon using an active locomotion capsule endoscope, which can be applied for a clinical site in the future. |
| first_indexed | 2024-03-10T06:37:45Z |
| format | Article |
| id | doaj.art-9b5c98b4b2294e06a25b0cda99c99fed |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T06:37:45Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-9b5c98b4b2294e06a25b0cda99c99fed2023-11-22T17:58:09ZengMDPI AGDiagnostics2075-44182021-10-011110187810.3390/diagnostics11101878Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility StudyManh Cuong Hoang0Kim Tien Nguyen1Jayoung Kim2Jong-Oh Park3Chang-Sei Kim4School of Mechanical Engineering, Chonnam National University, Gwangju 61186, KoreaKorea Institute of Medical Microrobotics, Gwangju 61011, KoreaKorea Institute of Medical Microrobotics, Gwangju 61011, KoreaKorea Institute of Medical Microrobotics, Gwangju 61011, KoreaSchool of Mechanical Engineering, Chonnam National University, Gwangju 61186, KoreaThis paper presents an active locomotion capsule endoscope system with 5D position sensing and real-time automated polyp detection for small-bowel and colon applications. An electromagnetic actuation system (EMA) consisting of stationary electromagnets is utilized to remotely control a magnetic capsule endoscope with multi-degree-of-freedom locomotion. For position sensing, an electronic system using a magnetic sensor array is built to track the position and orientation of the magnetic capsule during movement. The system is integrated with a deep learning model, named YOLOv3, which can automatically identify colorectal polyps in real-time with an average precision of 85%. The feasibility of the proposed method concerning active locomotion and localization is validated and demonstrated through in vitro experiments in a phantom duodenum. This study provides a high-potential solution for automatic diagnostics of the bowel and colon using an active locomotion capsule endoscope, which can be applied for a clinical site in the future.https://www.mdpi.com/2075-4418/11/10/1878active locomotion capsule endoscopemagnetic capsule endoscopecapsule localizationpolyp detectiondeep learning |
| spellingShingle | Manh Cuong Hoang Kim Tien Nguyen Jayoung Kim Jong-Oh Park Chang-Sei Kim Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study Diagnostics active locomotion capsule endoscope magnetic capsule endoscope capsule localization polyp detection deep learning |
| title | Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study |
| title_full | Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study |
| title_fullStr | Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study |
| title_full_unstemmed | Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study |
| title_short | Automated Bowel Polyp Detection Based on Actively Controlled Capsule Endoscopy: Feasibility Study |
| title_sort | automated bowel polyp detection based on actively controlled capsule endoscopy feasibility study |
| topic | active locomotion capsule endoscope magnetic capsule endoscope capsule localization polyp detection deep learning |
| url | https://www.mdpi.com/2075-4418/11/10/1878 |
| work_keys_str_mv | AT manhcuonghoang automatedbowelpolypdetectionbasedonactivelycontrolledcapsuleendoscopyfeasibilitystudy AT kimtiennguyen automatedbowelpolypdetectionbasedonactivelycontrolledcapsuleendoscopyfeasibilitystudy AT jayoungkim automatedbowelpolypdetectionbasedonactivelycontrolledcapsuleendoscopyfeasibilitystudy AT jongohpark automatedbowelpolypdetectionbasedonactivelycontrolledcapsuleendoscopyfeasibilitystudy AT changseikim automatedbowelpolypdetectionbasedonactivelycontrolledcapsuleendoscopyfeasibilitystudy |