Ulcer Detection in Image Converted from Video Footage of Wireless Capsule Endoscopy

Mamun, Abdullah Al; Hossain, Md. Sohag

doi:10.1109/icasert.2019.8934597

Cited by 10 publications

(2 citation statements)

References 12 publications

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“…Color threshold techniques on different color spaces have been applied for detecting different abnormalities. However, it couldn't distinguish the informative portion from the background for all the images [17][18][19][20][21][22].…”

Section: Related Workmentioning

confidence: 99%

Bleeding recognition technique in wireless capsule endoscopy images using fuzzy logic and principal component analysis

Mamun

Ping

Ghosh

et al. 2021

IJECE

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Wireless capsule endoscopy is the most innovative technology to perceive the entire gastrointestinal (GI) tract in recent times. It can diagnose inner diseases like bleeding, ulcer, tumor, Crohn's disease, and polyps. in a discretion way. It creates immense pressure and onus for clinicians to perceive a huge number of image frames, which is time-consuming and makes human oversight errors. Therefore a computer-automated system has been introduced for bleeding detection. A unique fuzzy logic technique is proposed to extract the specified bleeding and non-bleeding information from the image data. A particular quadratic support vector machine (QSVM) classifier is employed to classify the obtained statistical features from the bleeding and non-bleeding images incorporating principal component analysis (PCA). After extensive experiments on clinical data, 98% sensitivity, 98.4% accuracy, 98% specificity, 93% precision, 95.4% F1-score, and 99% negative predicted value have been achieved, which outperforms some of the states of art methods in this regard. It is optimistic that the proposed methodology would significantly contribute to bleeding detection techniques and diminish the additional onus of the physicians.

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Section: Related Workmentioning

confidence: 99%

Bleeding recognition technique in wireless capsule endoscopy images using fuzzy logic and principal component analysis

Mamun

Ping

Ghosh

et al. 2021

IJECE

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show abstract

Section: Relative Workmentioning

confidence: 99%

Small intestine bleeding detection using color threshold and morphological operation in WCE images

Mamun

Hossain

Ping

et al. 2021

IJECE

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<span>Wireless capsule endoscopy (WCE) is a significant modern technique for observing the whole gastroenterological tract to diagnose various diseases like bleeding, ulcer, tumor, Crohn's disease, polyps etc in a non-invasive manner. However, it will make a substantial onus for physicians like human oversight errors with time consumption for manual checking of a vast amount of image frames. These problems motivate the researchers to employ a computer-aided system to classify the particular information from the image frames. Therefore, a computer-aided system based on the color threshold and morphological operation has been proposed in this research to recognize specified bleeding images from the WCE. Besides, A unique classifier, quadratic support vector machine (QSVM) has been employed for classifying the bleeding and non-bleeding images with the statistical feature vector in HSV color space. After extensive experiments on clinical data, 95.8% accuracy, 95% sensitivity, 97% specificity, 80% precision, 99% negative predicted value and 85% F1 score has been achieved, which outperforms some of the existing methods in this regard. It is expected that this methodology would bring a significant contribution to the WCE technology. </span>

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Ulcer Detection in Wireless Capsule Endoscopy Using Locally Computed Features

Hossain

Mamun

Ghosh

et al. 2020

Cyber Security and Computer Science

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Ulcer Detection in Image Converted from Video Footage of Wireless Capsule Endoscopy

Cited by 10 publications

References 12 publications

Bleeding recognition technique in wireless capsule endoscopy images using fuzzy logic and principal component analysis

Bleeding recognition technique in wireless capsule endoscopy images using fuzzy logic and principal component analysis

Small intestine bleeding detection using color threshold and morphological operation in WCE images

Ulcer Detection in Wireless Capsule Endoscopy Using Locally Computed Features

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