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.

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 An Automatic Bleeding Frame and Region Detection Scheme for Wireless Capsule Endoscopy Videos Based on Interplane Intensity Variation Profile in Normalized RGB Color Space

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Amit Kumar Kundu ◽  
Shaikh Anowarul Fattah ◽  
Mamshad Nayeem Rizve
Keyword(s):  
Capsule Endoscopy ◽  
Color Space ◽  
Intensity Variation ◽  
Human Perception ◽  
Wireless Capsule Endoscopy ◽  
Morphological Operations ◽  
Detection Scheme ◽  
Bleeding Detection ◽  
Rgb Color Space ◽  
Wireless Capsule

Wireless capsule endoscopy (WCE) is an effective video technology to diagnose gastrointestinal (GI) disease, such as bleeding. In order to avoid conventional tedious and risky manual review process of long duration WCE videos, automatic bleeding detection schemes are getting importance. In this paper, to investigate bleeding, the analysis of WCE images is carried out in normalized RGB color space as human perception of bleeding is associated with different shades of red. In the proposed method, at first, from the WCE image frame, an efficient region of interest (ROI) is extracted based on interplane intensity variation profile in normalized RGB space. Next, from the extracted ROI, the variation in the normalized green plane is presented with the help of histogram. Features are extracted from the proposed normalized green plane histograms. For classification purpose, the K-nearest neighbors classifier is employed. Moreover, bleeding zones in a bleeding image are extracted utilizing some morphological operations. For performance evaluation, 2300 WCE images obtained from 30 publicly available WCE videos are used in a tenfold cross-validation scheme and the proposed method outperforms the reported four existing methods having an accuracy of 97.86%, a sensitivity of 95.20%, and a specificity of 98.32%.

Wireless Capsule Endoscopy – Uses Beyond GI Bleeding?

Endoscopy ◽  
2006 ◽  
Vol 38 (11) ◽  
Author(s):  
P McConville ◽  
WJ Cash ◽  
RGP Watson ◽  
JS Collins
Keyword(s):  
Capsule Endoscopy ◽  
Wireless Capsule Endoscopy ◽  
Gi Bleeding ◽  
Wireless Capsule

The Role of Wireless Capsule Endoscopy (WCE) in the Detection of Occult Primary Neuroendocrine Tumors

2017 ◽  
Vol 26 (2) ◽  
pp. 151-156
Author(s):  
Manuele Furnari ◽  
Andrea Buda ◽  
Gabriele Delconte ◽  
Davide Citterio ◽  
Theodor Voiosu ◽  
...  
Keyword(s):  
Neuroendocrine Tumor ◽  
Neuroendocrine Tumors ◽  
Capsule Endoscopy ◽  
Primary Tumor ◽  
Diagnostic Yield ◽  
Somatostatin Receptor ◽  
Tertiary Care ◽  
Wireless Capsule Endoscopy ◽  
First Line ◽  
Wireless Capsule

Background & Aims: Neuroendocrine tumors (NETs) are a heterogeneous group of neoplasms with unclear etiology that may show functioning or non-functioning features. Primary tumor localization often requires integrated imaging. The European Neuroendocrine Tumors Society (ENETS) guidelines proposed wireless-capsule endoscopy (WCE) as a possible diagnostic tool for NETs, if intestinal origin is suspected. However, its impact on therapeutic management is debated. We aimed to evaluate the yield of WCE in detecting intestinal primary tumor in patients showing liver NET metastases when first-line investigations are inconclusive.Method: Twenty-four patients with histological diagnosis of metastatic NET from liver biopsy and no evidence of primary lesions at first-line investigations were prospectively studied in an ENETS-certified tertiary care center. Wireless-capsule endoscopy was requested before explorative laparotomy and intra-operative ultrasound. The diagnostic yield of WCE was compared to the surgical exploration.Results: Sixteen subjects underwent surgery; 11/16 had positive WCE identifying 16 bulging lesions. Mini-laparotomy found 13 NETs in 11/16 patients (9 small bowel, 3 pancreas, 1 bile ducts). Agreement between WCE and laparotomy was recorded in 9 patients (Sensitivity=75%; Specificity=37.5%; PPV=55%; NPV=60%). Correspondence assessed per-lesions produced similar results (Sensitivity=70%; Specificity=25%; PPV=44%; NPV=50%). No capsule retentions were recorded.Conclusions: Wireless-capsule endoscopy is not indicated as second-line investigation for patients with gastro-entero-pancreatic NETs. In the setting of a referral center, it might provide additional information when conventional investigations are inconclusive about the primary site.Abbreviations: DBE: double balloon enteroscopy; GEP-NET: gastro-entero-pancreatic neuroendocrine tumor; GI: gastrointestinal; ENETS: European Neuroendocrine Tumor Society; NET: neuroendocrine tumor; SSRS: somatostatin receptor scintigraphy; WCE: wireless capsule endoscopy.

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