Publication | Closed Access
Automatic organs' detection in WCE
12
Citations
14
References
2012
Year
Automatic OrgansEngineeringFeature DetectionBiometricsGastroenterologyImage ClassificationImage AnalysisData SciencePattern RecognitionRadiologyHealth SciencesMachine VisionComputer-assisted SurgeryMedical ImagingStatistic FeaturesHaralick FeaturesGi TechniqueComputer ScienceMedical Image ComputingWireless Capsule EndoscopyComputer VisionComputer-aided DiagnosisMedical Image Analysis
Wireless capsule endoscopy (WCE) views the entire gastrointestinal (GI) tract. A main problem associated with this novel device is that too many frames must be reviewed by physicians. Thus it is essential to find an automatic and intelligent method to help physicians. One of the problems in WCE is its difficulty to distinguish among different organ's tissues. So, we introduce two novel algorithms which are able to classify main organs (among esophagus, stomach, small bowel and colon) in WCE's frames. In order to obtain our aim, we use statistic features (Haralick features) and non-statistic features (different diagrams and Gabor filter banks), colored features and non-colored features. Our experimental studies indicate good results that are shown in conclusion.
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