Researcher of Region Growing Medical Image Segmentation Based on Adaboost Algorithm

Peng Wang; X.F. Ye; Shi Wei Yin; Shao Chen Kang; Jing Lei Xin

doi:10.4028/www.scientific.net/AMR.142.21

Paper Titles

Technology and Characteristic of Wool Ring Spun Compound Yarn
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A Co-Evolutionary Contract Net-Based Framework for Distributed Manufacturing Execution Systems
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The Research on Cutting Force in High-Speed Milling Process of Aluminum Alloy Impeller
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Research of Asynchronous Multi-Type Sensors Data Fusion
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Researcher of Region Growing Medical Image Segmentation Based on Adaboost Algorithm
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Trail Investigation on Chip of High-Speed and Dry Cutting on Hardened Steel with PCBN Tool
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Simulate Measure for Spring Back of Autobody Panel's Edge
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Reconfigurable Clamping Device Based on Memory Alloy, Orientation Disc, Majority Column and Telescopic Pole
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Analysis of Mechanical Characteristics and Structural Options of Micro-Milling Cutter
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Researcher of Region Growing Medical Image Segmentation Based on Adaboost Algorithm

Abstract:

To obtain better region extraction results of medical image, a new segmentation algorithm is proposed based on improved Adaboost algorithm. The seed pixel is selected with background subtraction. The neighborhood point is judged. The primary selected seed is calibrated with label, and then the range of seed is reduced through growing label and the maximal saliency. The optimized Adaboost algorithm is taken as growing criterion to optimally combine the scrappy region when the region growing is over. The experiment result shows that the accuracy and robustness of the algorithm both meet the actual application required.