Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4

capsule endoscopy Related Publications

4 Image Processing Using Color and Object Information for Wireless Capsule Endoscopy

Authors: Gilwon Yoon, Yong-Gyu Lee, Jin-Hee Park

Abstract:

Wireless capsule endoscopy provides real-time images in the digestive tract. Capsule images are usually low resolution and are diverse images due to travel through various regions of human body. Color information has been a primary reference in predicting abnormalities such as bleeding. Often color is not sufficient for this purpose. In this study, we took morphological shapes into account as additional, but important criterion. First, we processed gastric images in order to indentify various objects in the image. Then, we analyzed color information in the object. In this way, we could remove unnecessary information and increase the accuracy. Compared to our previous investigations, we could handle images of various degrees of brightness and improve our diagnostic algorithm.

Keywords: Image Processing, object identification, capsule endoscopy, HSV model, Color Separation

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3 Improvement of Blood Detection Accuracy using Image Processing Techniques suitable for Capsule Endoscopy

Authors: Gilwon Yoon, Yong-Gyu Lee

Abstract:

Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.

Keywords: Image Processing, capsule endoscopy, blood detection

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2 Real-Time Image Analysis of Capsule Endoscopy for Bleeding Discrimination in Embedded System Platform

Authors: Gilwon Yoon, Yong-Gyu Lee

Abstract:

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

Keywords: Image Processing, Bleeding, capsule endoscopy, real time analysis

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1 Bleeding Detection Algorithm for Capsule Endoscopy

Authors: Gilwon Yoon, Yong-Gyu Lee

Abstract:

Automatic detection of bleeding is of practical importance since capsule endoscopy produces an extremely large number of images. Algorithm development of bleeding detection in the digestive tract is difficult due to different contrasts among the images, food dregs, secretion and others. In this study, were assigned weighting factors derived from the independent features of the contrast and brightness between bleeding and normality. Spectral analysis based on weighting factors was fast and accurate. Results were a sensitivity of 87% and a specificity of 90% when the accuracy was determined for each pixel out of 42 endoscope images.

Keywords: Image Analysis, Bleeding, capsule endoscopy, weighted spectrum

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