Computer-aided colorectal tumor classification in NBI endoscopy using local features

Tamaki, Toru; Yoshimuta, Junki; Kawakami, Misato; Raytchev, Bisser; Kaneda, Kazufumi; Yoshida, Shigeto; Takemura, Y; Onji, Keiichi; Miyaki, Rie; Tanaka, Shinji

doi:10.1016/j.media.2012.08.003

Cited by 128 publications

(74 citation statements)

References 154 publications

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“…In that respect, content-based visual information retrieval (CBVIR) has become an attractive technique for computer-aided diagnosis [19,21,5,33,42,53,40,54,51]. Actually, CBVIR consists in retrieving the most visually similar images based on the characteristics of their visual content.…”

Section: Introductionmentioning

confidence: 99%

Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex

Ahmed¹,

Mizotin²,

Benois-Pineau³

et al. 2015

Computerized Medical Imaging and Graphics

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Section: Introductionmentioning

confidence: 99%

Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex

Ahmed¹,

Mizotin²,

Benois-Pineau³

et al. 2015

Computerized Medical Imaging and Graphics

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“…A combination of computer-based assessments of polyps with NBI and Zoom was introduced in 2013 and showed an accuracy rate of 96% [97]. In 2015, the combination of NBI and zoom technology showed promising results with a negative predictive value of 96% for assessment of non-neoplastic polyps in the rectosigmoid [98].…”

Section: Technical Aspectsmentioning

confidence: 99%

Endoscopic Improvement of the Adenoma Detection Rate during Colonoscopy - Where Do We Stand in 2015?

Floer

Meister²

2016

Digestion

238

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Background: The presence of colorectal adenomas is considered a major risk factor for colorectal cancer development. The implementation of screening colonoscopy programs in the Western world has led to a substantial reduction of colorectal cancer death. Many efforts have been made to reduce the adenoma miss rates by the application of new endoscopic devices and techniques for better adenoma visualization. Summary: This special review gives the readership an overview of current endoscopic innovations that can aid in the increase of the adenoma detection rate (ADR) during colonoscopy. These innovations include the use of devices like EndoCuff® and EndoRings® as well as new technical equipment like third-eye endoscope® and full-spectrum endoscopy (FUSE®). Key Message: Technical improvements and newly developed accessories are able to improve the ADR. However, additional costs and a willingness to invest into potentially expensive equipment might be necessary. Investigator-dependent skills remain the backbone in the ADR detection.

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“…Each feature value for a given direction θ from the scale of N × N [pixel] image that has g gray levels is expressed in Formulas (12)-(16), assuming T is the sum of the elements of the run length matrix (11). …”

Section: Linementioning

confidence: 99%

Endoscope image analysis method for evaluating the extent of early gastric cancer

Hiroyasu

Hayashinuma

Yagi

et al. 2014

2014 IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP)

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In this study, a system is proposed to help physicians perform processing on images taken with a magnifying endoscopy with narrow band imaging. In our proposed system, the transition from lesion to normal zone is quantitatively analyzed and presented by texture analysis. Eleven feature values are calculated, i.e., six from a co-occurrence matrix and five from a run length matrix with a scanning window. Integrating these feature values formulates an effective and representative feature value, which is used to draw a color map, so the transition from lesion to normal zone can be visibly illustrated. In this paper, the proposed method is applied to images, and the efficacy is considered. This method is also applied to some rotated images to examine whether it could work effectively on such images.

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Computer-aided colorectal tumor classification in NBI endoscopy using local features

Cited by 128 publications

References 154 publications

Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex

Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex

Endoscopic Improvement of the Adenoma Detection Rate during Colonoscopy - Where Do We Stand in 2015?

Endoscope image analysis method for evaluating the extent of early gastric cancer

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