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PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence imaging
Fu LD(符礼丹)1,2; Lu BC3; Tian J1,2,4,5; Hu ZH1,2
Source PublicationComputerized Medical Imaging and Graphics
2023
Pages102216
Abstract

Fluorescence imaging has demonstrated great potential for malignant tissue inspection. However, poor imaging quality of medical fluorescent images inevitably brings challenges to disease diagnosis. Though improvement of image quality can be achieved by translating the images from low-quality domain to high-quality domain, fewer scholars have studied the spectrum translation and the prevalent cycle-consistent generative adversarial network (CycleGAN) is powerless to grasp local and semantic details, leading to produce unsatisfactory translated images. To enhance the visual quality by shifting spectrum and alleviate the under-constraint problem of CycleGAN, this study presents the design and construction of the perception-enhanced spectrum shift GAN (PSSGAN). Besides, by introducing the constraint of perceptual module and relativistic patch, the model learns effective biological structure details of image translation. Moreover, the interpolation technique is innovatively employed to validate that PSSGAN can vividly show the enhancement process and handle the perception-fidelity trade-off dilemma of fluorescent images. A novel no reference quantitative analysis strategy is presented for medical images. On the open data and collected sets, PSSGAN provided 15.32%~35.19% improvement in structural similarity and 21.55%~27.29% improvement in perceptual quality over the leading method CycleGAN. Extensive experimental results indicated that our PSSGAN achieved superior performance and exhibited vital clinical significance.

Indexed BySCIE
Language英语
Funding ProjectNational Natural Science Foundation of China (NSFC)[81930053]
Sub direction classification生物特征识别
planning direction of the national heavy laboratory视觉信息处理
Paper associated data
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57400
Collection中国科学院分子影像重点实验室
Corresponding AuthorTian J; Hu ZH
Affiliation1.CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
3.Department of Precision Instrument, Tsinghua University, Beijing 100084, China
4.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, 100191, China
5.Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an 710071, China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Fu LD,Lu BC,Tian J,et al. PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence imaging[J]. Computerized Medical Imaging and Graphics,2023:102216.
APA Fu LD,Lu BC,Tian J,&Hu ZH.(2023).PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence imaging.Computerized Medical Imaging and Graphics,102216.
MLA Fu LD,et al."PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence imaging".Computerized Medical Imaging and Graphics (2023):102216.
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