標題: Medical Image Segmentation with Adjustable Computational Complexity Using Data Density Functionals
作者: Chen, Chien-Chang
Tsai, Meng-Yuan
Kao, Ming-Ze
Lu, Henry Horng-Shing
統計學研究所
丘成桐中心
Institute of Statistics
Shing-Tung Yau Center
關鍵字: data density functionals;denoising;image segmentation;image compression
公開日期: 2-四月-2019
摘要: Featured Application The research work proposes an avenue of image segmentation that can simultaneously reduce computational complexity and filter image pollution for clinical investigations. Abstract Techniques of automatic medical image segmentation are the most important methods for clinical investigation, anatomic research, and modern medicine. Various image structures constructed from imaging apparatus achieve a diversity of medical applications. However, the diversified structures are also a burden of contemporary techniques. Performing an image segmentation with a tremendously small size (<25 pixels by 25 pixels) or tremendously large size (>1024 pixels by 1024 pixels) becomes a challenge in perspectives of both technical feasibility and theoretical development. Noise and pixel pollution caused by the imaging apparatus even aggravate the difficulty of image segmentation. To simultaneously overcome the mentioned predicaments, we propose a new method of medical image segmentation with adjustable computational complexity by introducing data density functionals. Under this theoretical framework, several kernels can be assigned to conquer specific predicaments. A square-root potential kernel is used to smoothen the featured components of employed images, while a Yukawa potential kernel is applied to enhance local featured properties. Besides, the characteristic of global density functional estimation also allows image compression without losing the main image feature structures. Experiments on image segmentation showed successful results with various compression ratios. The computational complexity was significantly improved, and the score of accuracy estimated by the Jaccard index had a great outcome. Moreover, noise and regions of light pollution were mostly filtered out in the procedure of image compression.
URI: http://dx.doi.org/10.3390/app9081718
http://hdl.handle.net/11536/152340
DOI: 10.3390/app9081718
期刊: APPLIED SCIENCES-BASEL
Volume: 9
Issue: 8
起始頁: 0
結束頁: 0
顯示於類別:期刊論文