An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Detecting Abnormal Patterns in WCE Images
BIBE '05 Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering
A Neural Network-Based Detection of Bleeding in Sequences of WCE Images
BIBE '05 Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
The usage of soft-computing methodologies in interpreting capsule endoscopy
Engineering Applications of Artificial Intelligence
Active Blood Detection in a High Resolution Capsule Endoscopy using Color Spectrum Transformation
BMEI '08 Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01
Computers in Biology and Medicine
Texture analysis for ulcer detection in capsule endoscopy images
Image and Vision Computing
Computer-aided tumor detection in endoscopic video using color wavelet features
IEEE Transactions on Information Technology in Biomedicine
MR Imaging and Osteoporosis: Fractal Lacunarity Analysis of Trabecular Bone
IEEE Transactions on Information Technology in Biomedicine
MPEG-7 Visual Descriptors—Contributions for Automated Feature Extraction in Capsule Endoscopy
IEEE Transactions on Circuits and Systems for Video Technology
Personalized identification of abdominal wall hernia meshes on computed tomography
Computer Methods and Programs in Biomedicine
Texture and color based image segmentation and pathology detection in capsule endoscopy videos
Computer Methods and Programs in Biomedicine
Stereoscopic visualization of laparoscope image using depth information from 3D model
Computer Methods and Programs in Biomedicine
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Wireless capsule endoscopy (WCE) is a novel imaging technique that is gradually gaining ground as it enables the non-invasive and efficacious visualization of the digestive track, and especially the entire small bowel including its middle part. However, the task of reviewing the vast amount of images produced by a WCE examination is a burden for the physicians. To tackle this major drawback, an innovative scheme for discriminating endoscopic images related to one of the most common intestinal diseases, ulceration, is presented here. This new approach focuses on colour-texture features in order to investigate how the structure information of healthy and abnormal tissue is distributed on RGB, HSV and CIE Lab colour spaces. The WCE images are pre-processed using bidimensional ensemble empirical mode decomposition so as to facilitate differential lacunarity analysis to extract the texture patterns of normal and ulcerous regions. Experimental results demonstrated promising classification performance (mean accuracy95%), exhibiting a high potential towards automatic WCE image analysis.