Abstract

The 5th International Conference on Biomedical Engineering and Biotechnology (ICBEB 2016)

Highlights

  • Accurate segmentation of Region of interest (Region of Interest, regions of interest (ROIs)) has an important place in medical image analysis, and still remains a challenge task because of the complex background and structure

  • Our analysis showed that the fractional anisotropy (FA) values are lower (P < 0.01), the radical diffusivity (RD) and mean diffusivity (MD) values are elevated (P < 0.01), and the Alzheimer’s disease (AD) values are Invariant (P > 0.05) in the patients’ body of the corpus callosum (CC)

  • Our hybrid system combines the advantages of support vector machine (SVM) and convolutional neural network (CNN), which are both widely used for image recognition

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Summary

Introduction

Accurate segmentation of Region of interest (Region of Interest, ROI) has an important place in medical image analysis, and still remains a challenge task because of the complex background and structure. Materials and methods This paper proposed a novel active contour model based on localizing region for ROI segmentation in capsule endoscopy images. Features in regions centered on an active contour were used to compute the local region descriptors. For calculating the local energies, the image was separated by the initial circular shape curve into two parts: interior and exterior. Each local region is fitted with a model to optimize the energies

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