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Journal Abstract Search

242 related items for PubMed ID: 33180722

  • 1. A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability.
    Zhou Y, Wang B, Huang L, Cui S, Shao L.
    IEEE Trans Med Imaging; 2021 Mar; 40(3):818-828. PubMed ID: 33180722
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  • 2. SSMD-UNet: semi-supervised multi-task decoders network for diabetic retinopathy segmentation.
    Ullah Z, Usman M, Latif S, Khan A, Gwak J.
    Sci Rep; 2023 Jun 05; 13(1):9087. PubMed ID: 37277554
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  • 3. DR-GAN: Conditional Generative Adversarial Network for Fine-Grained Lesion Synthesis on Diabetic Retinopathy Images.
    Zhou Y, Wang B, He X, Cui S, Shao L.
    IEEE J Biomed Health Inform; 2022 Jan 05; 26(1):56-66. PubMed ID: 33332280
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  • 4. Simple methods for the lesion detection and severity grading of diabetic retinopathy by image processing and transfer learning.
    Sugeno A, Ishikawa Y, Ohshima T, Muramatsu R.
    Comput Biol Med; 2021 Oct 05; 137():104795. PubMed ID: 34488028
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  • 5. Joint Learning of Multi-Level Tasks for Diabetic Retinopathy Grading on Low-Resolution Fundus Images.
    Wang X, Xu M, Zhang J, Jiang L, Li L, He M, Wang N, Liu H, Wang Z.
    IEEE J Biomed Health Inform; 2022 May 05; 26(5):2216-2227. PubMed ID: 34648460
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  • 7. A new retinal OCT-angiography diabetic retinopathy dataset for segmentation and DR grading.
    Ma F, Wang S, Dai C, Qi F, Meng J.
    J Biophotonics; 2023 Nov 05; 16(11):e202300052. PubMed ID: 37421596
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  • 10. Deep image mining for diabetic retinopathy screening.
    Quellec G, Charrière K, Boudi Y, Cochener B, Lamard M.
    Med Image Anal; 2017 Jul 05; 39():178-193. PubMed ID: 28511066
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  • 12. IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.
    Porwal P, Pachade S, Kokare M, Deshmukh G, Son J, Bae W, Liu L, Wang J, Liu X, Gao L, Wu T, Xiao J, Wang F, Yin B, Wang Y, Danala G, He L, Choi YH, Lee YC, Jung SH, Li Z, Sui X, Wu J, Li X, Zhou T, Toth J, Baran A, Kori A, Chennamsetty SS, Safwan M, Alex V, Lyu X, Cheng L, Chu Q, Li P, Ji X, Zhang S, Shen Y, Dai L, Saha O, Sathish R, Melo T, Araújo T, Harangi B, Sheng B, Fang R, Sheet D, Hajdu A, Zheng Y, Mendonça AM, Zhang S, Campilho A, Zheng B, Shen D, Giancardo L, Quellec G, Mériaudeau F.
    Med Image Anal; 2020 Jan 05; 59():101561. PubMed ID: 31671320
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  • 14. Combining transfer learning with retinal lesion features for accurate detection of diabetic retinopathy.
    Hassan D, Gill HM, Happe M, Bhatwadekar AD, Hajrasouliha AR, Janga SC.
    Front Med (Lausanne); 2022 Jan 05; 9():1050436. PubMed ID: 36425113
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  • 15. CANet: Cross-Disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading.
    Li X, Hu X, Yu L, Zhu L, Fu CW, Heng PA.
    IEEE Trans Med Imaging; 2020 May 05; 39(5):1483-1493. PubMed ID: 31714219
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  • 20. Automatic severity grade classification of diabetic retinopathy using deformable ladder Bi attention U-net and deep adaptive CNN.
    Durai DBJ, Jaya T.
    Med Biol Eng Comput; 2023 Aug 05; 61(8):2091-2113. PubMed ID: 37338737
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