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Wang Z, Song Y, Zhao B, Zhong Z, Yao L, Lv F, Li B, Hu Y. A Soft-Reference Breast Ultrasound Image Quality Assessment Method That Considers the Local Lesion Area. Bioengineering (Basel) 2023; 10:940. [PMID: 37627825 PMCID: PMC10451797 DOI: 10.3390/bioengineering10080940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 07/23/2023] [Accepted: 08/03/2023] [Indexed: 08/27/2023] Open
Abstract
The quality of breast ultrasound images has a significant impact on the accuracy of disease diagnosis. Existing image quality assessment (IQA) methods usually use pixel-level feature statistical methods or end-to-end deep learning methods, which focus on the global image quality but ignore the image quality of the lesion region. However, in clinical practice, doctors' evaluation of ultrasound image quality relies more on the local area of the lesion, which determines the diagnostic value of ultrasound images. In this study, a global-local integrated IQA framework for breast ultrasound images was proposed to learn doctors' clinical evaluation standards. In this study, 1285 breast ultrasound images were collected and scored by experienced doctors. After being classified as either images with lesions or images without lesions, they were evaluated using soft-reference IQA or bilinear CNN IQA, respectively. Experiments showed that for ultrasound images with lesions, our proposed soft-reference IQA achieved PLCC 0.8418 with doctors' annotation, while the existing end-to-end deep learning method that did not consider the local lesion features only achieved PLCC 0.6606. Due to the accuracy improvement for the images with lesions, our proposed global-local integrated IQA framework had better performance in the IQA task than the existing end-to-end deep learning method, with PLCC improving from 0.8306 to 0.8851.
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Affiliation(s)
- Ziwen Wang
- School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China;
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (Y.S.); (L.Y.); (Y.H.)
| | - Yuxin Song
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (Y.S.); (L.Y.); (Y.H.)
| | - Baoliang Zhao
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (Y.S.); (L.Y.); (Y.H.)
| | - Zhaoming Zhong
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China (F.L.)
- Department of Ultrasound, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Liang Yao
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (Y.S.); (L.Y.); (Y.H.)
| | - Faqin Lv
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China (F.L.)
- Department of Ultrasound, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Bing Li
- School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China;
| | - Ying Hu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; (Y.S.); (L.Y.); (Y.H.)
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Anton M, Veldkamp WJH, Hernandez-Giron I, Elster C. RDI[Formula: see text]a regression detectability index for quality assurance in: x-ray imaging. Phys Med Biol 2020; 65:085017. [PMID: 32109907 DOI: 10.1088/1361-6560/ab7b2e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Novel iterative image reconstruction methods can help reduce the required radiation dose in x-ray diagnostics such as computed tomography (CT), while maintaining sufficient image quality. Since some of the established image quality measures are not appropriate for reliably judging the quality of images derived by iterative methods, alternative approaches such as task-specific quality assessment would be highly desirable for acceptance or constancy testing. Task-based image quality methods are also closer to tasks performed by the radiologists, such as lesion detection. However, this approach is usually hampered by a huge workload, since hundreds of images are usually required for its application. It is demonstrated that the proposed approach works reliably on the basis of significantly fewer images, and that it correlates well with results obtained from human observers.
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Affiliation(s)
- M Anton
- Physikalisch-Technische Bundesanstalt Braunschweig and Berlin, Berlin, Germany
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Zhang F, Zhang B, Zhang R, Zhang X. SPCM: Image quality assessment based on symmetry phase congruency. Appl Soft Comput 2020. [DOI: 10.1016/j.asoc.2019.105987] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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