A modified Tseng algorithm approach to restoring thoracic diseases' computerized tomography images

被引：2
|
作者：
Ozsahin, Dilber Uzun [1 ,2 ,3 ]
Adamu, Abubakar [3 ,4 ]
Aliyu, Maryam Rabiu [5 ]
Umar, Huzaifa [3 ]
机构：
[1] Univ Sharjah, Coll Hlth Sci, Dept Med Diagnost Imaging, Sharjah, U Arab Emirates
[2] Univ Sharjah, Res Inst Med & Hlth Sci, Sharjah, U Arab Emirates
[3] Near East Univ, Operat Res Ctr Healthcare, Nicosia, Turkiye
[4] African Univ Sci & Technol, Charles Chidume Math Inst, Abuja, Nigeria
[5] Cyprus Int Univ, Dept Energy Syst Engn, Nicosia, Turkiye
来源：
PLOS ONE | 2024年 / 19卷 / 07期
关键词：
NOISE REMOVAL; SUPPORT; MRI;
D O I：
10.1371/journal.pone.0305728
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. Finally, the study demonstrates the potential to advance monotone inclusion problem-solving, particularly in the field of medical image recovery.
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收藏
页数：12
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