A non-uniform quantization scheme for visualization of CT images

作     者：Mehmood, Anam Khan, Ishtiaq Rasool Dawood, Hassan Dawood, Hussain 

作者机构：Univ Jeddah Coll Comp Sci & Engn Dept Comp Sci & Artificial Intelligence Jeddah Saudi Arabia Univ Engn & Technol Dept Software Engn Taxila Pakistan Univ Jeddah Coll Comp Sci & Engn Dept Comp & Network Engn Jeddah Saudi Arabia 

出 版 物：《MATHEMATICAL BIOSCIENCES AND ENGINEERING》 (Math. Biosci. Eng.)

年 卷 期：2021年第18卷第4期

页      面：4311-4326页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：Deputyship for Research & Innovation  Ministry of Education in Saudi Arabia [MoE-IF-G-20-11] 

主　　题：Clustering algorithm computed tomography high dynamic range tone-mapping medical image enhancement 

摘      要：Medical science heavily depends on image acquisition and post-processing for accurate diagnosis and treatment planning. The introduction of noise degrades the visual quality of the medical images during the capturing process, which may result in false perception. Therefore, medical image enhancement is an essential topic of research for the improvement of image quality. In this paper, a clustering-based contrast enhancement technique is presented for computed tomography (CT) images. Our approach uses the recursive splitting of data into clusters targeting the maximum error reduction in each cluster. This leads to grouping similar pixels in every cluster, maximizing inter-cluster and minimizing intra-cluster similarities. A suitable number of clusters can be chosen to represent high precision data with the desired bit-depth. We use 256 clusters to convert 16-bit CT scans to 8-bit images suitable for visualization on standard low dynamic range displays. We compare our method with several existing contrast enhancement algorithms and show that the proposed technique provides better results in terms of execution efficiency and quality of enhanced images.