PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence
文献类型：期刊论文
| 作者 | Fu, Lidan1,5; Lu, Binchun4; Tian, Jie1,2,3,5 ; Hu, Zhenhua1,5
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| 刊名 | COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
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| 出版日期 | 2023-07-01 |
| 卷号 | 107页码:11 |
| ISSN号 | 0895-6111 |
| 关键词 | Medical image enhancement Fluorescence imaging Cycle-consistent generative adversarial network No-reference metric |
| DOI | 10.1016/j.compmedimag.2023.102216 |
| 通讯作者 | Tian, Jie(tian@ieee.org) |
| 英文摘要 | 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% & SIM; 35.19% improvement in structural similarity and 21.55% & SIM; 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. |
| WOS关键词 | IMAGE ; RESOLUTION |
| 资助项目 | National Natural Science Foundation of China (NSFC)[62027901] ; National Natural Science Foundation of China (NSFC)[81930053] ; National Natural Science Foundation of China (NSFC)[81227901] ; National Natural Science Foundation of China (NSFC)[JCTD-2021-08] ; CAS Youth Interdisciplinary Team[HLHPTP 201703] ; Zhuhai High-level Health Personnel Team Project ; [92059207] |
| WOS研究方向 | Engineering ; Radiology, Nuclear Medicine & Medical Imaging |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:001053813500001 |
| 资助机构 | National Natural Science Foundation of China (NSFC) ; CAS Youth Interdisciplinary Team ; Zhuhai High-level Health Personnel Team Project |
| 源URL | [http://ir.ia.ac.cn/handle/173211/54143]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 通讯作者 | Tian, Jie |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China 2.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian 710071, Peoples R China 3.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Engn Med, Beijing 100191, Peoples R China 4.Tsinghua Univ, Dept Precis Instrument, Beijing 100084, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fu, Lidan,Lu, Binchun,Tian, Jie,et al. PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence[J]. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS,2023,107:11. |
| APA | Fu, Lidan,Lu, Binchun,Tian, Jie,&Hu, Zhenhua.(2023).PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence.COMPUTERIZED MEDICAL IMAGING AND GRAPHICS,107,11. |
| MLA | Fu, Lidan,et al."PSSGAN: Towards spectrum shift based perceptual quality enhancement for fluorescence".COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 107(2023):11. |
入库方式： OAI收割
来源：自动化研究所
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