ICMIR 2017: Recent Developments in Mechatronics and Intelligent Robotics pp 299-307 | Cite as
A Minimum Distance Cluster Based on Region Growing Method
Abstract
In order to acquire accurately virtual 3D human models, the region of interest (ROI) on medical images is separately segmented out. The proposed method based on region growing algorithms, at first plots adjacent regions around ROIs by rectangles. Then, the seed of each region is detected as centers. To make the method grow at a correct region, the ROI seed is selected which evolves in the direction of eight neighbors under the limit of minimum distance. Finally, depended on the seeds enlargements of ROI, a whole organ are extracted out. In experiments, the segmentation result is compared with an image thresholding method based on minimizing the measures of fuzziness (TMMF). Quantitative evaluation is performed within acceptable limits using volumetric overlap error (VOE) and relative volume difference (RVD).
Keywords
Minimum distance cluster Image segmentation Region growing Image thresholdingNotes
Acknowledgments
The authors would like to thank the associate editor and the anonymous reviewers for their careful work and valuable suggestions for this paper. This work was supported by Provincial Key Foundation for Excellent Young Talents of Colleges and Universities of Anhui (No.2013SQRL063ZD), Key University Science Research Project of Anhui Province (KJ2017A927 and KJ2017A926) and the National Natural Science Foundation of China under Grant No. 61573022.
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