Publication | Closed Access
Image segmentation of pyramid style identifier based on Support Vector Machine for colorectal endoscopic images
11
Citations
4
References
2015
Year
Unknown Venue
EngineeringBiometricsDigital PathologyEndoscopic ImagingSupport Vector MachineImage ClassificationImage AnalysisPattern RecognitionColorectal Cancer PatientsComputational ImagingEdge DetectionPyramid Style IdentifierRadiologyMachine VisionMedical ImagingColorectal CancerComputational PathologyComputer EngineeringComputer ScienceMedical Image ComputingComputer VisionComputer-aided DiagnosisClinical Image AnalysisMedicineMedical Image AnalysisImage SegmentationNarrow Band Imaging
With the increase of colorectal cancer patients in recent years, the needs of quantitative evaluation of colorectal cancer are increased, and the computer-aided diagnosis (CAD) system which supports doctor's diagnosis is essential. In this paper, a hardware design of type identification module in CAD system for colorectal endoscopic images with narrow band imaging (NBI) magnification is proposed for real-time processing of full high definition image (1920 × 1080 pixel). A pyramid style image segmentation with SVMs for multi-size scan windows, which can be implemented on an FPGA with small circuit area and achieve high accuracy, is proposed for actual complex colorectal endoscopic images.
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