论文信息 - Image segmentation of pyramid style identifier based on Support Vector Machine for colorectal endoscopic images

Image segmentation of pyramid style identifier based on Support Vector Machine for colorectal endoscopic images

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.

[1] Nello Cristianini,et al. Large Margin DAGs for Multiclass Classification , 1999, NIPS.

[2] Anh-Tuan Hoang,et al. FPGA implementation of type identifier for colorectal endoscopie images with NBI magnification , 2014, 2014 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS).

[3] Shinji Tanaka,et al. Narrow-band imaging magnification predicts the histology and invasion depth of colorectal tumors. , 2009, Gastrointestinal endoscopy.

[4] Kazufumi Kaneda,et al. Computer-Aided Colorectal Tumor Classification in NBI Endoscopy Using CNN Features , 2016, ArXiv.

[5] Vladimir Vapnik,et al. Statistical learning theory , 1998 .

[6] Anh-Tuan Hoang,et al. FPGA implementation of feature extraction for colorectal endoscopic images with NBI magnification , 2014, 2014 IEEE International Symposium on Circuits and Systems (ISCAS).