AIMC Topic: Capsule Endoscopy
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Reducing reading time and assessing disease in capsule endoscopy videos: A deep learning approach.
International journal of medical informatics
Jan 14, 2025
BACKGROUND: The wireless capsule endoscope (CE) is a valuable diagnostic tool in gastroenterology, offering a safe and minimally invasive visualization of the gastrointestinal tract. One of the few drawbacks identified by the gastroenterology communi...
The Use of Artificial Intelligence for Endoscopic Evaluation of the Small Bowel.
Gastrointestinal endoscopy clinics of North America
Jan 8, 2025
There remains great potential for widespread implementation of artificial intelligence (AI) in managing small bowel disorders. Studies have shown excellent accuracy in diagnosing various diseases and lesions throughout the small bowel, with most show...
Toward automated small bowel capsule endoscopy reporting using a summarizing machine learning algorithm: The SUM UP study.
Clinics and research in hepatology and gastroenterology
Nov 30, 2024
BACKGROUND AND OBJECTIVES: Deep learning (DL) algorithms demonstrate excellent diagnostic performance for the detection of vascular lesions via small bowel (SB) capsule endoscopy (CE), including vascular abnormalities with high (P2), intermediate (P1...
Establishing an AI model and application for automated capsule endoscopy recognition based on convolutional neural networks (with video).
BMC gastroenterology
Nov 6, 2024
BACKGROUND: Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, the need to process a vast number of images imposes a significant workload on physicians, leading to a high risk of missed diagnoses. This study aims t...
Review of Deep Learning Performance in Wireless Capsule Endoscopy Images for GI Disease Classification.
F1000Research
Sep 23, 2024
Wireless capsule endoscopy is a non-invasive medical imaging modality used for diagnosing and monitoring digestive tract diseases. However, the analysis of images obtained from wireless capsule endoscopy is a challenging task, as the images are of lo...
Characterizing the Coefficient of Friction Between a Capsule Robot and the Colon.
IEEE transactions on bio-medical engineering
Sep 19, 2024
OBJECTIVE: A capsule robot (CR) with an onboard active locomotion mechanism, has been developed as a promising alternative to colonoscopy due to its minimally-invasive advantage. Predicting the traction force and locomotion resistance of the CR, whic...
AI-KODA score application for cleanliness assessment in video capsule endoscopy frames.
Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Aug 13, 2024
BACKGROUND: Currently, there is no automated method for assessing cleanliness in video capsule endoscopy (VCE). Our objectives were to automate the process of evaluating and collecting medical scores of VCE frames according to the existing KOrea-Cana...
A new artificial intelligence system for both stomach and small-bowel capsule endoscopy.
Gastrointestinal endoscopy
Jun 6, 2024
BACKGROUND AND AIMS: Despite the benefits of artificial intelligence in small-bowel (SB) capsule endoscopy (CE) image reading, information on its application in the stomach and SB CE is lacking.
Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet.
Journal of imaging informatics in medicine
Apr 8, 2024
Capsule endoscopy (CE) is non-invasive and painless during gastrointestinal examination. However, capsule endoscopy can increase the workload of image reviewing for clinicians, making it prone to missed and misdiagnosed diagnoses. Current researches ...
Automated detection of small bowel lesions based on capsule endoscopy using deep learning algorithm.
Clinics and research in hepatology and gastroenterology
Apr 4, 2024
BACKGROUND: In order to overcome the challenges of lesion detection in capsule endoscopy (CE), we improved the YOLOv5-based deep learning algorithm and established the CE-YOLOv5 algorithm to identify small bowel lesions captured by CE.
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