Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence imaging | |
Fu LD(符礼丹)1,2![]() ![]() ![]() | |
发表期刊 | Computerized Medical Imaging and Graphics
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2023 | |
页码 | 102216 |
摘要 | 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. |
收录类别 | SCIE |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China (NSFC)[81930053] |
七大方向——子方向分类 | 生物特征识别 |
国重实验室规划方向分类 | 视觉信息处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57400 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Tian J; Hu ZH |
作者单位 | 1.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 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 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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