Abnormality detection in retinal image by individualized background learning
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Benzhi Chen | Lisheng Wang | Jian Sun | Zongben Xu | Xiuying Wang | David Dagan Feng | Yijie Huang | Jian Sun | Xiuying Wang | Zongben Xu | D. Feng | Lisheng Wang | Benzhi Chen | Yijie Huang
[1] Lei Zhang,et al. A Cyclic Weighted Median Method for L1 Low-Rank Matrix Factorization with Missing Entries , 2013, AAAI.
[2] Subhashini Venugopalan,et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. , 2016, JAMA.
[3] Yi Ma,et al. Robust principal component analysis? , 2009, JACM.
[4] Amir Sadeghipour,et al. Artificial intelligence in retina , 2018, Progress in Retinal and Eye Research.
[5] Benzhi Chen,et al. Weakly Supervised Lesion Detection From Fundus Images , 2019, IEEE Transactions on Medical Imaging.
[6] Xudong Jiang,et al. Blood vessel segmentation from fundus image by a cascade classification framework , 2019, Pattern Recognit..
[7] András Hajdu,et al. Retinal Microaneurysm Detection Through Local Rotating Cross-Section Profile Analysis , 2013, IEEE Transactions on Medical Imaging.
[8] Daniel Rueckert,et al. Multiple Sclerosis Lesion Segmentation Using Dictionary Learning and Sparse Coding , 2013, MICCAI.
[9] Pascale Massin,et al. A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina , 2002, IEEE Transactions on Medical Imaging.
[10] M. Sonka,et al. Retinal Imaging and Image Analysis. , 2010, IEEE transactions on medical imaging.
[11] Gwénolé Quellec,et al. Automatic detection of referral patients due to retinal pathologies through data mining , 2016, Medical Image Anal..
[12] Benzhi Chen,et al. Automatic Detection of Longitudinal Changes for Retinal Fundus Images Based on Low-Rank Decomposition , 2018 .
[13] Michael Elad,et al. Sparse and Redundant Representations - From Theory to Applications in Signal and Image Processing , 2010 .
[14] Gwénolé Quellec,et al. Deep image mining for diabetic retinopathy screening , 2016, Medical Image Anal..
[15] Desire Sidibé,et al. Discrimination of retinal images containing bright lesions using sparse coded features and SVM , 2015, Comput. Biol. Medicine.
[16] Fawnizu Azmadi Hussin,et al. Localization of optic disc and fovea in retinal images using intensity based line scanning analysis , 2017, Comput. Biol. Medicine.
[17] Wei Bu,et al. Optic disc segmentation based on variational model with multiple energies , 2017, Pattern Recognit..
[18] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[19] Santi P. Maity,et al. Automatic Detection of Retinal Lesions for Screening of Diabetic Retinopathy , 2018, IEEE Transactions on Biomedical Engineering.
[20] Alexandru Telea,et al. An Image Inpainting Technique Based on the Fast Marching Method , 2004, J. Graphics, GPU, & Game Tools.
[21] Lei Zhang,et al. Robust Online Matrix Factorization for Dynamic Background Subtraction , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Shehzad Khalid,et al. Identification and classification of microaneurysms for early detection of diabetic retinopathy , 2013, Pattern Recognit..
[23] Zhiwu Lu,et al. Noise-robust semi-supervised learning via fast sparse coding , 2015, Pattern Recognit..
[24] Jayanthi Sivaswamy,et al. Automatic assessment of macular edema from color retinal images , 2012, IEEE Transactions on Medical Imaging.
[25] U. Rajendra Acharya,et al. Computer-aided diagnosis of diabetic retinopathy: A review , 2013, Comput. Biol. Medicine.
[26] Sansanee Auephanwiriyakul,et al. Diagnosis of diabetic retinopathy based on holistic texture and local retinal features , 2019, Inf. Sci..
[27] Jayanthi Sivaswamy,et al. Detection and discrimination of disease-related abnormalities based on learning normal cases , 2012, Pattern Recognit..
[28] Nobuhiro Oda,et al. Usefulness of computerized method for lung nodule detection on digital chest radiographs using similar subtraction images from different patients. , 2012, European journal of radiology.
[29] Yao Wang,et al. Low-Rank Matrix Factorization under General Mixture Noise Distributions , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[30] Badrinath Roysam,et al. Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.
[31] Lei Zhang,et al. Robust Principal Component Analysis with Complex Noise , 2014, ICML.
[32] Bram van Ginneken,et al. Fast Convolutional Neural Network Training Using Selective Data Sampling: Application to Hemorrhage Detection in Color Fundus Images , 2016, IEEE Transactions on Medical Imaging.
[33] Sharib Ali,et al. Statistical atlas based exudate segmentation , 2013, Comput. Medical Imaging Graph..
[34] Xiaoqiang Lu,et al. Structured dictionary learning for abnormal event detection in crowded scenes , 2018, Pattern Recognit..
[35] Raymond H. Chan,et al. A Primal–Dual Method for Total-Variation-Based Wavelet Domain Inpainting , 2012, IEEE Transactions on Image Processing.
[36] Shouren Lan,et al. Diverse lesion detection from retinal images by subspace learning over normal samples , 2018, Neurocomputing.
[37] Christos Davatzikos,et al. Individualized statistical learning from medical image databases: Application to identification of brain lesions , 2014, Medical Image Anal..
[38] Guillermo Sapiro,et al. Online Learning for Matrix Factorization and Sparse Coding , 2009, J. Mach. Learn. Res..