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A New Model to Determine Asymmetry Coefficients on MR Images using PSNR and SSIM | |
Ozic, Muhammet Usame; Ozsen, Seral | |
通讯作者 | Ozic, Muhammet Usame |
会议名称 | 2017 International Artificial Intelligence and Data Processing Symposium (IDAP) |
会议日期 | SEP 16-17, 2017 |
会议地点 | Malatya, TURKEY |
英文摘要 | The human brain consists of two hemispheres, right and left. These two hemispheres are almost symmetrical, not perfectly. However, in neurological diseases, the volumetric losses in the brain begin to deteriorate asymmetrically between the two hemispheres. This deterioration can be local or global in the brain. Symmetry deterioration can be a biomarker in the early stage diagnosis and the following of neurological diseases. However, it has been stated that the analysis of asymmetry in the brain by numerical methods is problematic. In this study, a new approach is proposed to analyze the brain symmetry deterioration numerically. In order to perform asymmetry analysis in MR images, two hemispheres must be separated from each other by finding the midsagittal plane which are known symmetry axis. The PSNR and SSIM coefficients are often used for quality measurements between two images. In the study, these coefficients were tested for asymmetry measurement. Statistical analysis was performed by determining PSNR-SSIM coefficients between 70 Control and 70 Alzheimer Disease MR images from the OASIS database. It was determined that the use of PSNR and SSIM coefficients in the asymmetry analysis of MR images gave meaningful results. |
英文关键词 | Asymmetry Alzheimer MR PSNR SSIM |
来源出版物 | 2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP) |
出版年 | 2017 |
EISBN | 978-1-5386-1880-6 |
出版者 | IEEE |
类型 | Proceedings Paper |
语种 | 英语 |
国家 | Turkey |
收录类别 | CPCI-S |
WOS记录号 | WOS:000426868700041 |
WOS关键词 | GRAY-MATTER ASYMMETRIES ; ALZHEIMERS-DISEASE ; ATROPHY |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications |
WOS研究方向 | Computer Science |
资源类型 | 会议论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/306177 |
作者单位 | Selcuk Univ, Elect Elect Engn, Konya, Turkey |
推荐引用方式 GB/T 7714 | Ozic, Muhammet Usame,Ozsen, Seral. A New Model to Determine Asymmetry Coefficients on MR Images using PSNR and SSIM[C]:IEEE,2017. |
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