scholarly journals Performance of Predictive Coders for Wireless Capsule Endoscopy Image Compression

2020 ◽  
Vol 8 (5) ◽  
pp. 3094-3098
Keyword(s):  
Small Bowel ◽  
Capsule Endoscopy ◽  
Signal To Noise Ratio ◽  
Predictive Coding ◽  
Diagnostic Technique ◽  
Endoscopic Examination ◽  
Wireless Capsule Endoscopy ◽  
Neighboring Pixel ◽  
Highly Correlated ◽  
Wireless Capsule

Wireless capsule endoscopy is a medical diagnostic technique developed for the endoscopic examination of the small bowel. The encoder module is the core of the wireless capsule endoscopic system impacting on power and area requirement for the hardware implementation of the capsule. One of the remarkable features of the endoscopic image is that the neighboring pixels are highly correlated. Two predictive coding techniques are considered in this work exploiting the above fact. The first predictive coder i.e., DPCM coder is based on previous horizontal neighboring pixel, whereas the second predictive coder is based on adjacent horizontal and diagonal neighbors. The performance of the predictive coders is tested with 41 small bowel type endoscopic images available in the Gastrolab dataset. The results show that the average compression rate and peak signal to noise ratio attained by DPCM coder and newly tested predictive coder are 66.37 % & 73.03 % and 32.17 dB & 35.55 dB, respectively

scholarly journals Wireless Capsule Endoscopy in Small Bowel Crohn’s Disease

2016 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Subasinghege Dona Lilanthi Padmika Subasinghe ◽  
Nawagamuwage Iresha Chandima Perera ◽  
Asoka Ratnatilaka
Keyword(s):  
Crohn’S Disease ◽  
Small Bowel ◽  
Crohn's Disease ◽  
Capsule Endoscopy ◽  
Wireless Capsule Endoscopy ◽  
Wireless Capsule

M2A Wireless Capsule Endoscopy Versus Enteroclysis; A Prospective Study in 68 Patients with Suspected Small Bowel Disease

2004 ◽  
Vol 59 (5) ◽  
pp. P147 ◽  
Author(s):  
Periklis Apostolopoulos ◽  
Eleftheria Giannakoulopoulou ◽  
Ioannis S. Papanikolaou ◽  
Georgios Alexandrakis ◽  
X. Papacharalampous ◽  
...  
Keyword(s):  
Small Bowel ◽  
Prospective Study ◽  
Capsule Endoscopy ◽  
Bowel Disease ◽  
Wireless Capsule Endoscopy ◽  
Small Bowel Disease ◽  
A Prospective Study ◽  
Wireless Capsule

scholarly journals DINOSARC: Color Features Based on Selective Aggregation of Chromatic Image Components for Wireless Capsule Endoscopy

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Michael D. Vasilakakis ◽  
Dimitris K. Iakovidis ◽  
Evaggelos Spyrou ◽  
Anastasios Koulaouzidis
Keyword(s):  
Capsule Endoscopy ◽  
Saliency Detection ◽  
Diagnostic Technique ◽  
Wireless Capsule Endoscopy ◽  
Salient Point ◽  
Detection Scheme ◽  
Level Information ◽  
Point Detection ◽  
Wireless Capsule ◽  
Selective Aggregation

Wireless Capsule Endoscopy (WCE) is a noninvasive diagnostic technique enabling the inspection of the whole gastrointestinal (GI) tract by capturing and wirelessly transmitting thousands of color images. Proprietary software “stitches” the images into videos for examination by accredited readers. However, the videos produced are of large length and consequently the reading task becomes harder and more prone to human errors. Automating the WCE reading process could contribute in both the reduction of the examination time and the improvement of its diagnostic accuracy. In this paper, we present a novel feature extraction methodology for automated WCE image analysis. It aims at discriminating various kinds of abnormalities from the normal contents of WCE images, in a machine learning-based classification framework. The extraction of the proposed features involves an unsupervised color-based saliency detection scheme which, unlike current approaches, combines both point and region-level saliency information and the estimation of local and global image color descriptors. The salient point detection process involves estimation of DIstaNces On Selective Aggregation of chRomatic image Components (DINOSARC). The descriptors are extracted from superpixels by coevaluating both point and region-level information. The main conclusions of the experiments performed on a publicly available dataset of WCE images are (a) the proposed salient point detection scheme results in significantly less and more relevant salient points; (b) the proposed descriptors are more discriminative than relevant state-of-the-art descriptors, promising a wider adoption of the proposed approach for computer-aided diagnosis in WCE.

A Steerable Mechanism for Wireless Capsule Endoscopy

2007 ◽  
Author(s):  
Kamran Mohseni
Keyword(s):  
Small Bowel ◽  
Capsule Endoscopy ◽  
Gastrointestinal Disease ◽  
Wireless Capsule Endoscopy ◽  
Advanced Stages ◽  
Wireless Capsule ◽  
Exploratory Surgery ◽  
The Way

Gastrointestinal (GI) disease affects millions of people worldwide and costs billions of dollars annually. Because the symptoms of GI diseases are often vague, physicians are often presented with gastrointestinal disease in advanced stages. Because conventional endoscopes often cannot reach all the way through the 20-foot small bowel, exploratory surgery previously was necessary to enable physicians to complete their diagnosis.

scholarly journals Automatic detection of small bowel tumors in wireless capsule endoscopy images using ensemble learning

2019 ◽  
Vol 47 (1) ◽  
pp. 52-63 ◽  
Author(s):  
Pedro M. Vieira ◽  
Nuno R Freitas ◽  
João Valente ◽  
Ismael F. Vaz ◽  
Carla Rolanda ◽  
...  
Keyword(s):  
Small Bowel ◽  
Ensemble Learning ◽  
Capsule Endoscopy ◽  
Automatic Detection ◽  
Wireless Capsule Endoscopy ◽  
Small Bowel Tumors ◽  
Wireless Capsule
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