[1] GILLIES R J, KINAHAN P E, HRICAK H. Radiomics:images are more than pictures, they are data[J]. Radiology, 2015, 278(2):563-577. [2] QIU J J, WU Y, HUI B, et al. Textural analysis of liver focal lesions with co-occurrence matrix and wavelet transform on CT:a feasible study in FNH, HEM and HCC[EB/OL].[2018-05-10]. http://www.dpi-proceedings.com/index.php/dtetr/article/view/6733/6325. [3] PU Y F, ZHOU J L, YUAN X. Fractional differential mask:a fractional differential-based approach for multiscale texture enhancement[J]. IEEE Transactions on Image Processing, 2010, 19(2):491-511. [4] JALAB H A, IBRAHIM R W. Texture enhancement for medical images based on fractional differential masks[J]. Discrete Dynamics in Nature and Society, 2013, 2013:618536. [5] HALAVAARA J, BREUER J, AYUSO C, et al. Liver tumor characterization:comparison between liver-specific gadoxetic acid disodium-enhanced MRI and biphasic CT - a multicenter trial[J]. Journal of Computer Assisted Tomography, 2006, 30(3):345-354. [6] HASEBROOCK K M, SERKOVA N J. Toxicity of MRI and CT contrast agents[J]. Expert Opinion on Drug Metabolism & Toxicology, 2009, 5(4):403-416. [7] YANG Y, SU Z, SUN L. Medical image enhancement algorithm based on wavelet transform[J]. Electronics Letters, 2010, 46(2):120-121. [8] BHARDWAJ A, SINGH M K. A novel approach of medical image enhancement based on wavelet transform[J]. International Journal of Engineering Research and Applications, 2012, 2(3):2356-2360. [9] LAVANYA C, YUGANDHAR D. Medical image enhancement based on wavelet transform[J]. IOSR Journal of Electronics and Communication Engineering, 2016, 11(1):20-28. [10] PU Y, WANG W, ZHOU J, et al. Fractional differential approach to detecting textural features of digital image and its fractional differential filter implementation[J]. Science in China Series F:Information Sciences, 2008, 51(9):1319-1339. [11] 张涌, 蒲亦非, 周激流. 基于分数阶微分的图像增强模板[J]. 计算机应用研究, 2012, 29(8):3195-3197. (ZHANG Y, PU Y F, ZHOU J L. Image enhancement masks based on fractional differential[J]. Application Research of Computers, 2012, 29(8):3195-3197.) [12] LI B, XIE W. Adaptive fractional differential approach and its application to medical image enhancement[J]. Computers & Electrical Engineering, 2015, 45:324-335. [13] 陈向阳, 谭礼健. 基于自适应分数阶微分的医学图像增强算法[J]. 计算机应用研究, 2017, 34(12):3895-3898. (CHEN X Y, TAN L J. Medical image enhancement algorithm based on adaptive fractional order differentiation[J]. Application Research of Computers, 2017, 34(12):3895-3898.) [14] MALLAT S G. A theory for multiresolution signal decomposition:the wavelet representation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(7):674-693. [15] DAUBECHIES I. The wavelet transform, time-frequency localization and signal analysis[J]. IEEE Transactions on Information Theory, 1990, 36(5):961-1005. [16] OLDHAM K, SPANIER J. The Fractional Calculus Theory and Applications of Differentiation and Integration to Arbitrary Order[M]. Amsterdam:Elsevier, 1974. [17] GARG V, SINGH K. An improved Grunwald-Letnikov fractional differential mask for image texture enhancement[J]. International Journal of Advanced Computer Science and Applications, 2012, 3(3):130-135. [18] WANG J, LIU Z C, CHOROWSKI J, et al. Robust 3D action recognition wit random occupancy patters[C]//ECCV 2012:Proceedings of the 12th European Conference on Computer Vision, LNCS 7573. Berlin:Springer, 2012:872-885. [19] 吴瑞芳, 宣士斌, 荆奇. 基于局部特征的分数阶微分图像增强方法[J]. 计算机工程与应用, 2014, 50(3):160-164. (WU R F, XUAN S B, JING Q. Fractional differential image enhancement algorithm based on local feature[J]. Computer Engineering and Applications, 2014, 50(3):160-164.) |