A New Active Locomotion Capsule Endoscopy under Magnetic Control and Automated Reading Program

Oh, Dong Jun; Kim, Kwang Seop; Lim, Yun Jeong

doi:10.5946/ce.2020.127

Cited by 13 publications

(14 citation statements)

References 56 publications

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“…With the emergence of CE in 2000[ 17 ], it has revolutionized our understanding of small intestinal mucosa[ 18 - 20 ], enabling doctors to detect small intestinal mucosal erosion, ulcers, vascular disease, bleeding, polyps, parasite and other lesions more efficiently. However, reliable and rapid reading of video is still a challenge, but more and more studies have shown that the combination of AI and CE can greatly improve the efficiency of our evaluation of small intestinal mucosal lesions; the detection accuracy was above 90% in most studies[ 21 - 27 ].…”

Section: Ai In Small Intestine Anatomymentioning

confidence: 99%

Artificial intelligence in small intestinal diseases: Application and prospects

Yu¹,

Li²,

Yao³

et al. 2021

WJG

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The small intestine is located in the middle of the gastrointestinal tract, so small intestinal diseases are more difficult to diagnose than other gastrointestinal diseases. However, with the extensive application of artificial intelligence in the field of small intestinal diseases, with its efficient learning capacities and computational power, artificial intelligence plays an important role in the auxiliary diagnosis and prognosis prediction based on the capsule endoscopy and other examination methods, which improves the accuracy of diagnosis and prediction and reduces the workload of doctors. In this review, a comprehensive retrieval was performed on articles published up to October 2020 from PubMed and other databases. Thereby the application status of artificial intelligence in small intestinal diseases was systematically introduced, and the challenges and prospects in this field were also analyzed.

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Section: Ai In Small Intestine Anatomymentioning

confidence: 99%

Artificial intelligence in small intestinal diseases: Application and prospects

Yu¹,

Li²,

Yao³

et al. 2021

WJG

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“…Since 2010, deep learning and convolutional neural network (CNN) algorithms have been used in medicine. Currently, the CNN algorithm is being used as the dominant AI algorithm in the field of medical image reading [ 13 ]. As previously mentioned, it takes a lot of time and effort to read a capsule endoscopy.…”

Section: Application Of Artificial Intelligence (Ai) Into the Reading Of Small Bowel Capsule Endoscopy (Sbce)mentioning

confidence: 99%

“…However, these reading tools have a limitation in that they are less accurate than conventional reading [ 11 , 12 ]. Currently, lesion detection using an AI algorithm has emerged as a way to save reading time while maintaining the accuracy of lesion detection compared to conventional reading [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

A Current and Newly Proposed Artificial Intelligence Algorithm for Reading Small Bowel Capsule Endoscopy

Hwang

Lim

2021

Diagnostics

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Small bowel capsule endoscopy (SBCE) is one of the most useful methods for diagnosing small bowel mucosal lesions. However, it takes a long time to interpret the capsule images. To solve this problem, artificial intelligence (AI) algorithms for SBCE readings are being actively studied. In this article, we analyzed several studies that applied AI algorithms to SBCE readings, such as automatic lesion detection, automatic classification of bowel cleanliness, and automatic compartmentalization of small bowels. In addition to automatic lesion detection using AI algorithms, a new direction of AI algorithms related to shorter reading times and improved lesion detection accuracy should be considered. Therefore, it is necessary to develop an integrated AI algorithm composed of algorithms with various functions in order to be used in clinical practice.

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“…Unlike most other in-building magnetic-controlled capsule endoscopy systems developed in recent decades [ 5 , 6 , 7 , 8 ], the IMS MACE system is highly portable and thus provides a solution for physicians to perform upper GI endoscopy for patients outside hospital or clinic settings. It is known that peptic ulcer disease and esophageal reflux are common in the senior population [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Upper Gastrointestinal Examination in Home Care Setting with a Magnetically Assisted Capsule Endoscopy System: A Retrospective Study

et al. 2021

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The magnetic assisted capsule endoscope (MACE) with a hand-held magnetic field navigator (MFN) for upper gastrointestinal examination achieved satisfactory results in a healthy volunteer study. We evaluated the feasibility of upper gastrointestinal examination in the home care setting with the MACE system. Home care patients with upper gastrointestinal symptoms that received an MACE exam were enrolled in the study. MACE procedure time; completeness of observation of important anatomical landmarks; endoscopic diagnosis; patient tolerance during the procedure; and patient data, including age, sex, comorbidities, symptoms, body weight, and height, were retrieved from hospital information system for data analysis. A total of 16 participants were enrolled with a mean age 74.3 ± 15.4 years (47 to 99 years). One patient failed to swallow the capsule and was excluded. The average procedure time was 23.7 ± 10.0 min (14.1 to 42.5 min) to complete each endoscopic exam for the remaining 15 patients. The overall maneuverability in the esophagus, stomach, and duodenum was 93.75%, 87.5%, and 75%, respectively. Overall completeness in the aforementioned regions was 93.75%, 81.25%, and 75%, respectively. No severe adverse events were noted. The results clearly demonstrate the promise of using this MACE system to perform endoscopic examination outside the hospital for patients confined to the community and home.

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A New Active Locomotion Capsule Endoscopy under Magnetic Control and Automated Reading Program

Cited by 13 publications

References 56 publications

Artificial intelligence in small intestinal diseases: Application and prospects

Artificial intelligence in small intestinal diseases: Application and prospects

A Current and Newly Proposed Artificial Intelligence Algorithm for Reading Small Bowel Capsule Endoscopy

Feasibility of Upper Gastrointestinal Examination in Home Care Setting with a Magnetically Assisted Capsule Endoscopy System: A Retrospective Study

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