[1]殷夫,纪震,周家锐,等.PET/CT图像质量主观评价与感知模型[J].深圳大学学报理工版,2015,32(2):205-212.[doi:10.3724/SP.J.1249.2015.02205]
 Yin Fu,Ji Zhen,Zhou Jiarui,et al.Subjective assessment and perception model of PET/CT image quality[J].Journal of Shenzhen University Science and Engineering,2015,32(2):205-212.[doi:10.3724/SP.J.1249.2015.02205]
点击复制

PET/CT图像质量主观评价与感知模型()
分享到:

《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第32卷
期数:
2015年第2期
页码:
205-212
栏目:
电子与信息科学
出版日期:
2015-03-20

文章信息/Info

Title:
Subjective assessment and perception model of PET/CT image quality
文章编号:
201502013
作者:
殷夫1纪震1周家锐1张海婕2
1)深圳大学计算机与软件学院,深圳 518052
2)广州军区武汉陆军总医院核医学科,武汉 430070
Author(s):
Yin Fu1 Ji Zhen1 Zhou Jiarui1 and Zhang Haijie2
1) College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518052, P.R.China
2) Nuclear Medicine Department, Wuhan General Hospital of Guangzhou Military Command, Wuhan 430070, P.R.China
关键词:
计算机图像处理图像质量评价算法双重刺激失真水平测试法电子发射断层显像/计算机断层扫描特征相似性图像质量主观评价数据库
Keywords:
computer image processing image quality assessment double-stimulus impairment scale method positron emission tomography/computed tomography feature similarity subjective image quality assessment database
分类号:
TP 391.41; TP 391.77
DOI:
10.3724/SP.J.1249.2015.02205
文献标志码:
A
摘要:
针对面向医学领域的主观评价数据库缺乏,导致医学图像质量评价(image quality assessment, IQA)算法性能难以分析的问题,基于双重刺激失真水平测试法,建立正电子发射断层显像/计算机断层扫描医学图像的主观评价数据库.对比13种国际通用IQA算法在数据库上的性能,分析不同退化方法对IQA算法的影响.结果表明,对新建立的图像评价数据库来说,特征相似性(feature similarity,FSIM)图像评价模型在相关性及稳定性方面明显优于其他IQA算法,包括目前医学领域主流的峰值信噪比评价指标.
Abstract:
Image quality assessment (IQA) is highly dependent on subjective assessment. However, no subjective image quality assessment database is presently available for medical image, which poses a big challenge for the evaluation of medical IQA algorithms. In this paper, we propose the first positron emission tomography/computed tomography medical image subjective assessment database based on the double-stimulus impairment scale method. Performances of thirteen commonly used IQA algorithms are compared on the database. Moreover, effects of different image distortions on IQA algorithms are analyzed. Experimental results show that the feature similarity model outperforms other IQA methods, including peak signal to noise ratio, the most commonly used algorithm in the medical field.

参考文献/References:

[1] Wang Rongfu.PET/CT:new technology application of molecular imaging[M].Beijing:Beijing Medical University Press,2011:1-5.(in Chinese)
王荣福.PET/CT:分子影像学新技术应用[M].北京:北京大学医学出版社,2011:1-5.
[2] Chen Shengzu.PET/CT technology principle and oncology application[M].Beijing:People’s Military Medical Press,2007:3-10.(in Chinese)
陈盛祖.PET/CT技术原理及肿瘤学应用[M].北京:人民军医出版社,2007:3-10.
[3] Lin Chunyi,Yin Junxun,Gao Xue,et al.A multi-level medical image semantic modeling approach based on statistical learning[J].Journal of Shenzhen University Science and Engineering,2007,24(2):138-143.(in Chinese)
林春漪,尹俊勋,高学,等. 基于统计学习的多层医学图像语义建模方法[J].深圳大学学报理工版,2007,24(2):138-143.
[4] Zhou Jinchao,Dai Ruwei,Xiao Baihua.Overview of image quality assessment[J].Computer Science,2008,35(7):1-8.(in Chinese)
周景超,戴汝为,肖柏华.图像质量评价研究综述[J].计算机科学,2008,35(7):1-8.
[5] Zhang Min,Zhang Lei.Non-shift edge based ratio (NSER):an image quality assessment metric based on early vision features[J].IEEE Signal Processing Letters,2011,18(5):315.
[6] Hu Yuanyuan,Niu Xiamu.Image quality assessment based on human visibility threshold theory and structural similarity[J].Journal of Shenzhen University Science and Engineering,2010,27(2):185-191.(in Chinese)
胡媛媛,牛夏牧.基于视觉阈值的结构相似度图像质量评价算法[J].深圳大学学报理工,2010,27(2):185-191.
[7] Zhang Xuemin,Shu Hua.Outline of experimental psychology[M].Beijing:Beijing Normal University Publishing Group,2004.(in Chinese)
张学敏,舒华.实验心理学纲要[M].北京:北京师范大学出版社,2004.
[8] ITU.ITU-R_BT. 500-11Methodology for the subjective assessment of the quality of television pictures[S].
[9] Vu E C L,Chandler D M.Visual fixation patterns when judging image quality:effects of distortion type,amount,and subject experience[C]// IEEE Symposium on Image Analysis and Interpretation.Santa Fe(Argentina):IEEE Press,2008:73-76.
[10] Larson E C,Chandler D M.Most apparent distortion:full-reference image quality assessment and therole of strategy[J].Journal of Electronic Imaging,2010,19(1):011006-1-011006-21.
[11] Mou Xuanqin,Xue Wufeng,Zhang Min.Methods of partial reference image quality assessment based on early vision.CN101482973[P],China,2009.(in Chinese)
牟轩沁,薛武峰,张敏.基于早期视觉的部分参考图像质量评价方法[P]. CN101482973.中国,2009.
[12] Sheikh H R,Bovik A C,Veciana G de.An information fidelity criterion for image quality assessment using natural scene statistics[J].IEEE Transactions on Image Processing,2005,14(12):2117-2122.
[13] Sheikh H R,Bovik A C.Image information and visual quality[J].IEEE Transactions on Image Processing,2006,15(2):430-444.
[14] Wang Z,Bovik A C,Sheikh H R.Image quality assessment:from error measurement to structural similarity[J].IEEE Transactions on Image Processing,2004,13(4):600-612.
[15] Wang Zhou,Simoncelli E P,Bovik A C.Multi-scale structural similarity for image quality assessment[C]// Proceedings of the 37th IEEE AsilomarConference on Signals,Systems,and Computers.Pacific Grove(USA):IEEE Press,2003:1398-1402.
[16] Zhang Lin,Zhang Lei,Mou Xuanqin,et al.FSIM:a feature similarity index for image quality assessment[J].IEEE Transactions on Image Processing,2011,20(8):2378-2386.
[17] Damera-Venkata N,Kite T D,Geisler W S,et al.Image quality assessment based on a degradation model[J].IEEE Transactions on Image Processing,2000,9(4):636-650.
[18] Chandler D M,Hemami S S.VSNR:a wavelet-based visual signal-to-noise ratio for natural images[J].IEEE Transactions on Image Processing,2007,16(9):2284-2298.
[19] Xue Wufeng,Mou Xuanqin,Zhang Lei,et al.Blind image quality assessment using joint statistics of gradient magnitude and Laplacian features[J].IEEE Transactions on Image Processing,2014,23(11):4850-4862.
[20] Video Quality Experts Group.Final report from the video quality experts group on the validation of objective models of video quality assessment,Phase II[R/OL].(2003-08-25).http://www.vqeg.org/

相似文献/References:

[1]郭美钦,江健民.人脸图像风格迁移的改进算法[J].深圳大学学报理工版,2019,36(3):230.[doi:10.3724/SP.J.1249.2019.03230]
 GUO Meiqin and JIANG Jianmin.Spatially-robust image style transfer for headshot portraits[J].Journal of Shenzhen University Science and Engineering,2019,36(2):230.[doi:10.3724/SP.J.1249.2019.03230]
[2]贾志成,郑笑,郭艳菊,等.改进鲸群优化子空间匹配追踪的稀疏解混算法[J].深圳大学学报理工版,2020,37(1):63.[doi:10.3724/SP.J.1249.2020.01063]
 JIA Zhicheng,ZHENG Xiao,GUO Yanju,et al.Sparse unmixing using the improved whale optimized subspace matching pursuit algorithm[J].Journal of Shenzhen University Science and Engineering,2020,37(2):63.[doi:10.3724/SP.J.1249.2020.01063]

备注/Memo

备注/Memo:
基金项目:国家自然科学基金资助项目(u1201256)
作者简介:殷夫(1989—),男(汉族),湖北省汉川市人,深圳大学硕士研究生.E-mail:slintch@sina.com
引文:殷夫,纪震,周家锐,等.PET/CT图像质量主观评价与感知模型[J]. 深圳大学学报理工版,2015,32(2):205-212.
Received:2014-10-13;Accepted:2015-02-04
Foundation:National Natural Science Foundation of China(u1201256)
Corresponding author:Professor Ji Zhen.E-mail:jizhen@szu.edu.cn
Citation:Yin Fu,Ji Zhen,Zhou Jiarui,et al.Subjective assessment and perception model of PET/CT image quality[J]. Journal of Shenzhen University Science and Engineering, 2015, 32(2): 205-212.(in Chinese)
更新日期/Last Update: 2015-03-12