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Book ChapterDOI

Automatic Contrast Enhancement for Wireless Capsule Endoscopy Videos with Spectral Optimal Contrast-Tone Mapping

TLDR
An automatic contrast enhancement method for WCE videos by using an extension of the recently proposed optimal contrast-tone mapping (OCTM) to color images by utilizing the transformation of each RGB color from of the endoscopy video to the spectral color space La*b* and utilizing the OCTM on the intensity channel alone is obtained.
Abstract
Wireless capsule endoscopy (WCE) is a revolutionary imaging method for visualizing gastrointestinal tract in patients. Each exam of a patient creates large-scale color video data typically in hours and automatic computer aided diagnosis (CAD) are of important in alleviating the strain on expert gastroenterologists. In this work we consider an automatic contrast enhancement method for WCE videos by using an extension of the recently proposed optimal contrast-tone mapping (OCTM) to color images. By utilizing the transformation of each RGB color from of the endoscopy video to the spectral color space La*b* and utilizing the OCTM on the intensity channel alone we obtain our spectral OCTM (SOCTM) approach. Experimental results comparing histogram equalization, anisotropic diffusion and original OCTM show that our enhancement works well without creating saturation artifacts in real WCE imagery.

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Citations
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Journal ArticleDOI

Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

TL;DR: In this article, the authors review different polyp detection approaches for capsule endoscopy imagery and provide systematic analysis with challenges faced by standard image processing and computer vision methods, and provide a systematic analysis.
Journal ArticleDOI

Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

TL;DR: Different polyp detection approaches for VCE imagery are reviewed and systematic analysis with challenges faced by standard image processing and computer vision methods is provided.
Journal ArticleDOI

Human Visual System Consistent Model for Wireless Capsule Endoscopy Image Enhancement and Applications

TL;DR: A human visual system based image enhancement model that uses a feature-linking neural network model based on timing precisely of the spiking neurons is extended, indicating that it is viable to be used within a computer-aided diagnosis systems for GI tract diseases.
Book ChapterDOI

Automatic Mucosa Detection in Video Capsule Endoscopy with Adaptive Thresholding

TL;DR: An automatic tissue detection method that uses an adaptive entropy thresholding for better separation of mucosa which lines the colon wall from lumen, which is the hollowed gastrointestinal tract is considered.
Proceedings ArticleDOI

Vascularization features for polyp localization in capsule endoscopy

TL;DR: Using texture features computed from principle curvatures of the image surface, and multiscale directional vesselness stamping, localization of polyps is obtained from a given video frame using vascularization features.
References
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Journal ArticleDOI

Image Enhancement by Histogram transformation

TL;DR: In this article, a number of simple and inexpensive enhancement techniques are suggested to make use of easily computed local context, features to aid in the reassignment of each point's gray level during histogram transfomation.
Journal ArticleDOI

Computer-Aided Decision Support Systems for Endoscopy in the Gastrointestinal Tract: A Review

TL;DR: An introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract and a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.
Journal ArticleDOI

A Linear Programming Approach for Optimal Contrast-Tone Mapping

TL;DR: This paper proposes a novel algorithmic approach of image enhancement via optimal contrast-tone mapping that maximizes expected contrast gain subject to an upper limit on tone distortion and optionally to other constraints that suppress artifacts.
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