본문 바로가기
KERD
논문KCI 등재

The Future of Capsule Endoscopy: The Role of Artificial Intelligence and Other Technical Advancements

2

조회

0

다운로드

2

인용

0

참고문헌

키워드

주제분류내과학

초록

Capsule endoscopy has revolutionized the management of small-bowel diseases owing to its convenience and noninvasiveness. Capsule endoscopy is a common method for the evaluation of obscure gastrointestinal bleeding, Crohn’s disease, small-boweltumors, and polyposis syndrome. However, the laborious reading process, oversight of small-bowel lesions, and lack of locomotionare major obstacles to expanding its application. Along with recent advances in artificial intelligence, several studies have reportedthe promising performance of convolutional neural network systems for the diagnosis of various small-bowel lesions includingerosion/ulcers, angioectasias, polyps, and bleeding lesions, which have reduced the time needed for capsule endoscopy interpretation. Furthermore, colon capsule endoscopy and capsule endoscopy locomotion driven by magnetic force have been investigated forclinical application, and various capsule endoscopy prototypes for active locomotion, biopsy, or therapeutic approaches have beenintroduced. In this review, we will discuss the recent advancements in artificial intelligence in the field of capsule endoscopy, as wellas studies on other technological improvements in capsule endoscopy.

Abstract

Capsule endoscopy has revolutionized the management of small-bowel diseases owing to its convenience and noninvasiveness. Capsule endoscopy is a common method for the evaluation of obscure gastrointestinal bleeding, Crohn’s disease, small-boweltumors, and polyposis syndrome. However, the laborious reading process, oversight of small-bowel lesions, and lack of locomotionare major obstacles to expanding its application. Along with recent advances in artificial intelligence, several studies have reportedthe promising performance of convolutional neural network systems for the diagnosis of various small-bowel lesions includingerosion/ulcers, angioectasias, polyps, and bleeding lesions, which have reduced the time needed for capsule endoscopy interpretation. Furthermore, colon capsule endoscopy and capsule endoscopy locomotion driven by magnetic force have been investigated forclinical application, and various capsule endoscopy prototypes for active locomotion, biopsy, or therapeutic approaches have beenintroduced. In this review, we will discuss the recent advancements in artificial intelligence in the field of capsule endoscopy, as wellas studies on other technological improvements in capsule endoscopy.

참고문헌 (53)

  1. Iddan G, "Wireless capsule endoscopy", Nature, 405, pp.417~ (2000)
  2. Kopylov U, "Diagnostic modalities for the evaluation of small bowel disorders", Curr Opin Gastroenterol, 31, pp.111~117 (2015)
  3. Eliakim R, "Video capsule endoscopy of the small bowel", Curr Opin Gastroenterol, 29, pp.133~139 (2013)
  4. Pennazio M, "Small-bowel capsule endoscopy and device-assisted enteroscopy for diagnosis and treatment of small-bowel disorders : European Society of Gastrointestinal Endoscopy(ESGE)clinical guideline", Endoscopy, 47, pp.352~376 (2015)
  5. ASGE Technology Committee, "Wireless capsule endoscopy", Gastrointest Endosc, 78, pp.805~815 (2013)
  6. Yang YJ, "Application of artificial intelligence in gastroenterology", World J Gastroenterol, 25, pp.1666~1683 (2019)
  7. Horie Y, "Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks", Gastrointest Endosc, 89, pp.25~32 (2019)
  8. Cho BJ, "Automated classification of gastric neoplasms in endoscopic images using a convolutional neural network", Endoscopy, 51, pp.1121~1129 (2019)
  9. Wang P, "Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates : a prospective randomised controlled study", Gut, 68, pp.1813~1819 (2019)
  10. McAlindon ME, "Capsule endoscopy of the small bowel", Ann Transl Med, 4, pp.369~ (2016)
  11. Le Berre C, "Application of artificial Intelligence to gastroenterology and hepatology", Gastroenterology, 158, pp.76~94.e2 (2020)
  12. Liu G, "Detection of small bowel tumor based on multi-scale curvelet analysis and fractal technology in capsule endoscopy", Comput Biol Med, 70, pp.131~138 (2016)
  13. Li B, "Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection", IEEE Trans Inf Technol Biomed, 16, pp.323~329 (2012)
  14. Eid A, "A curvelet-based lacunarity approach for ulcer detection from wireless capsule endoscopy images", Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, pp.273~278 (2013), IEEE
  15. Yuan Y, "Saliency based ulcer detection for wireless capsule endoscopy diagnosis", IEEE Trans Med Imaging, 34, pp.2046~2057 (2015)
  16. Tenório JM, "Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease", Int J Med Inform, 80, pp.793~802 (2011)
  17. Li B, "Computer-based detection of bleeding and ulcer in wireless capsule endoscopy images by chromaticity moments", Comput Biol Med, 39, pp.141~147 (2009)
  18. Li B, "A comparative study of shape features for polyp detection in wireless capsule endoscopy images", Conf Proc IEEE Eng Med Biol Soc, 2009, pp.3731~3734 (2009)
  19. Sainju S, "Automated bleeding detection in capsule endoscopy videos using statistical features and region growing", J Med Syst, 38, pp.25~ (2014)
  20. Zhou T, "Quantitative analysis of patients with celiac disease by video capsule endoscopy : a deep learning method", Comput Biol Med, 85, pp.1~6 (2017)
  21. Wu X, "Automatic hookworm detection in wireless capsule endoscopy images", IEEE Trans Med Imaging, 35, pp.1741~1752 (2016)
  22. Noya F, "Automated angiodysplasia detection from wireless capsule endoscopy", Conf Proc IEEE Eng Med Biol Soc, 2017, pp.3158~3161 (2017)
  23. Hassan AR, "Computer-aided gastrointestinal hemorrhage detection in wireless capsule endoscopy videos", Comput Methods Programs Biomed, 122, pp.341~353 (2015)
  24. Chao WL, "Application of artificial intelligence in the detection and differentiation of colon polyps: a technical review for physicians", Diagnostics(Basel), 9, pp.99~ (2019)
  25. Aoki T, "Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network", Gastrointest Endosc, 89, pp.357~363 (2019)
  26. Aoki T, "Clinical usefulness of a deep learning-based system as the first screening on small-bowel capsule endoscopy reading", Dig Endosc, 32, pp.585~591 (2020)
  27. Klang E, "Deep learning algorithms for automated detection of Crohn’s disease ulcers by video capsule endoscopy", Gastrointest Endosc, 91, pp.606~613.e2 (2020)
  28. Leenhardt R, "A neural network algorithm for detection of GI angiectasia during small-bowel capsule endoscopy", Gastrointest Endosc, 89, pp.189~194 (2019)
  29. Tsuboi A, "Artificial intelligence using a convolutional neural network for automatic detection of small-bowel angioectasia in capsule endoscopy images", Dig Endosc, 32, pp.382~390 (2020)
  30. Aoki T, "Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network", J Gastroenterol Hepatol, 35, pp.1196~1200 (2020)
  31. Saito H, "Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network", Gastrointest Endosc, 92, pp.144~151.e1 (2020)
  32. Iakovidis DK, "Automatic lesion detection in capsule endoscopy based on color saliency : closer to an essential adjunct for reviewing software", Gastrointest Endosc, 80, pp.877~883 (2014)
  33. Ding Z, "Gastroenterologist-level identification of small-bowel diseases and normal variants by capsule endoscopy using a deep-learning model", Gastroenterology, 157, pp.1044~1054 (2019)
  34. Shelly Soffer, "Deep learning for wireless capsule endoscopy: a systematic review and meta-analysis", Gastrointestinal Endoscopy, 92(4), pp.831~839.e8 (2020), Elsevier BV[DOI]
  35. Spada C, "Accuracy of first-and second-generation colon capsules in endoscopic detection of colorectal polyps : a systematic review and meta-analysis", Clin Gastroenterol Hepatol, 14, pp.1533~1543.e8 (2016)
  36. Hall B, "PillCam COLON 2© as a pan-enteroscopic test in Crohn’s disease", World J Gastrointest Endosc, 7, pp.1230~1232 (2015)
  37. Ye CA, "PillCam colon capsule endoscopy versus conventional colonoscopy for the detection of severity and extent of ulcerative colitis", J Dig Dis, 14, pp.117~124 (2013)
  38. Li Z, "Robotic endoscopy", Visc Med, 34, pp.45~51 (2018)
  39. Shamsudhin N, "Magnetically guided capsule endoscopy", Med Phys, 44, pp.e91~e111 (2017)
  40. Zhao AJ, "Screening for gastric cancer with magnetically controlled capsule gastroscopy in asymptomatic individuals", Gastrointest Endosc, 88, pp.466~474.e1 (2018)
  41. Liao Z, "Accuracy of magnetically controlled capsule endoscopy, compared with conventional gastroscopy, in detection of gastric diseases", Clin Gastroenterol Hepatol, 14, pp.1266~1273. e1 (2016)
  42. Ching HL, "Diagnostic yield of magnetically assisted capsule endoscopy versus gastroscopy in recurrent and refractory iron deficiency anemia", Endoscopy, 51, pp.409~418 (2019)
  43. Beg S, "Diagnosis of Barrett’s esophagus and esophageal varices using a magnetically assisted capsule endoscopy system", Gastrointest Endosc, 91, pp.773~781. e1 (2020)
  44. Fontana R, "An innovative wireless endoscopic capsule with spherical shape", IEEE Trans Biomed Circuits Syst, 11, pp.143~152 (2017)
  45. Fu Q, "Conceptual design of a novel magnetically actuated hybrid microrobot", 2017 IEEE International Conference on Mechatronics and Automation (ICMA), pp.1001~1005 (2017), IEEE
  46. Guo J, "Development of a novel wireless spiral capsule robot with modular structure", 2017 IEEE International Conference on Mechatronics and Automation (ICMA), pp.439~444 (2017), IEEE
  47. Jang J, "4-Camera VGA-resolution capsule endoscope with 80Mb", s body-channel communication transceiver and Sub-cmrange capsule localization, 2018 (2018), 282~284[DOI]
  48. Demosthenous P, "Infrared fluorescence-based cancer screening capsule for the small intestine", IEEE Trans Biomed Circuits Syst, 10, pp.467~476 (2016)
  49. Yim S, "Biopsy using a magnetic capsule endoscope carrying, releasing, and retrieving untethered microgrippers", IEEE Trans Biomed Eng, 61, pp.513~521 (2014)
  50. Wen-Wen Chen, "Design of Micro Biopsy Device for Wireless Autonomous Endoscope", International Journal of Precision Engineering and Manufacturing, 15(11), pp.2317~2325 (2014), 한국정밀공학회
  51. Son D, "Magnetically actuated soft capsule endoscope for fine-needle aspiration biopsy", 2017 IEEE International Conference on Robotics and Automation (ICRA), pp.1132~1139 (2017), IEEE
  52. Stewart FR, "Development of a therapeutic capsule endoscope for treatment in the gastrointestinal tract: bench testing to translational trial", 2017 IEEE International Ultrasonics Symposium (IUS), pp.1~4 (2017), IEEE
  53. Leung BHK, "A therapeutic wireless capsule for treatment of gastrointestinal haemorrhage by balloon tamponade effect", IEEE Trans Biomed Eng, 64, pp.1106~1114 (2017)

관련 논문AI추천

이 간행물의 다른 논문 (20건)