Literature DB >> 22919250

Sensitivity of the suspected blood indicator: an experimental study.

Sung Chul Park1, Hoon Jai Chun, Eun Sun Kim, Bora Keum, Yeon Seok Seo, Yong Sik Kim, Yoon Tae Jeen, Hong Sik Lee, Soon Ho Um, Chang Duck Kim, Ho Sang Ryu.   

Abstract

AIM: To investigate whether suspected blood indicator (SBI) in capsule endoscopy (CE) is affected by background color and capsule passage velocity.
METHODS: Experimental models of the small intestine constructed from paper in a variety of colors were used to simulate the background colors observed in CE images. The background colors studied included very pale yellow, yellow, very pale magenta, light grayish pink, burnt sienna, and deep and dark brown, and red spots were attached inside them. An endoscopic capsule was manually passed through the models. The rate of detection of the red spots by the SBI was evaluated based on the colors of the models and the capsule passage velocities (0.5 cm/s, 1 cm/s, and 2 cm/s).
RESULTS: The rate of detection of the red spots by the SBI differed significantly according to the background color of the model (P < 0.001). Detection rates were highest for backgrounds of very pale magenta, burnt sienna, and yellow, in that order. They were lowest for backgrounds of dark brown and very pale yellow. The rate of detection of red spots by the SBI tended to decrease at rapid capsule passage velocities (1-2 cm/s) compared to slow velocities (0.5 cm/s) for backgrounds of very pale yellow (P = 0.042), yellow (P = 0.001), very pale magenta (P = 0.002), and burnt sienna (P = 0.001). No significant differences in the rate of detection were observed according to velocity for light grayish pink (P = 0.643) or dark brown (P = 0.396).
CONCLUSION: SBI sensitivity was affected by background color and capsule passage velocity in the models. These findings may facilitate the rapid detection of bleeding lesions by CE.

Entities:  

Keywords:  Background color; Capsule endoscopy; Passage velocity; Sensitivity; Suspected blood indicator

Mesh:

Year:  2012        PMID: 22919250      PMCID: PMC3422798          DOI: 10.3748/wjg.v18.i31.4169

Source DB:  PubMed          Journal:  World J Gastroenterol        ISSN: 1007-9327            Impact factor:   5.742


  21 in total

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6.  Multiple Linear Discriminant Models for Extracting Salient Characteristic Patterns in Capsule Endoscopy Images for Multi-Disease Detection.

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8.  Deep Transfer Learning for Automated Intestinal Bleeding Detection in Capsule Endoscopy Imaging.

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