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Journal Abstract Search

176 related items for PubMed ID: 37421596

  • 1. 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; 16(11):e202300052. PubMed ID: 37421596
    [Abstract] [Full Text] [Related]

  • 2. Advancing Diabetic Retinopathy Diagnosis: Leveraging Optical Coherence Tomography Imaging with Convolutional Neural Networks.
    Ahmed HS, Thrishulamurthy CJ.
    Rom J Ophthalmol; 2023 Nov; 67(4):398-402. PubMed ID: 38239418
    [Abstract] [Full Text] [Related]

  • 3. Automatic detection of microaneurysms in optical coherence tomography images of retina using convolutional neural networks and transfer learning.
    Almasi R, Vafaei A, Kazeminasab E, Rabbani H.
    Sci Rep; 2022 Aug 17; 12(1):13975. PubMed ID: 35978087
    [Abstract] [Full Text] [Related]

  • 4. The Role of Different Retinal Imaging Modalities in Predicting Progression of Diabetic Retinopathy: A Survey.
    Elsharkawy M, Elrazzaz M, Sharafeldeen A, Alhalabi M, Khalifa F, Soliman A, Elnakib A, Mahmoud A, Ghazal M, El-Daydamony E, Atwan A, Sandhu HS, El-Baz A.
    Sensors (Basel); 2022 May 04; 22(9):. PubMed ID: 35591182
    [Abstract] [Full Text] [Related]

  • 5. A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography.
    Ryu G, Lee K, Park D, Park SH, Sagong M.
    Sci Rep; 2021 Nov 26; 11(1):23024. PubMed ID: 34837030
    [Abstract] [Full Text] [Related]

  • 6. Ensembling U-Nets for microaneurysm segmentation in optical coherence tomography angiography in patients with diabetic retinopathy.
    Husvogt L, Yaghy A, Camacho A, Lam K, Schottenhamml J, Ploner SB, Fujimoto JG, Waheed NK, Maier A.
    Sci Rep; 2024 Sep 14; 14(1):21520. PubMed ID: 39277636
    [Abstract] [Full Text] [Related]

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  • 9. Detection of Diabetic Retinopathy Using Extracted 3D Features from OCT Images.
    Elgafi M, Sharafeldeen A, Elnakib A, Elgarayhi A, Alghamdi NS, Sallah M, El-Baz A.
    Sensors (Basel); 2022 Oct 15; 22(20):. PubMed ID: 36298186
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  • 11. 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 15; 137():104795. PubMed ID: 34488028
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  • 12. A novel approach for intelligent diagnosis and grading of diabetic retinopathy.
    Hai Z, Zou B, Xiao X, Peng Q, Yan J, Zhang W, Yue K.
    Comput Biol Med; 2024 Apr 15; 172():108246. PubMed ID: 38471350
    [Abstract] [Full Text] [Related]

  • 13. Automated Diagnosis of Optical Coherence Tomography Angiography (OCTA) Based on Machine Learning Techniques.
    Yasser I, Khalifa F, Abdeltawab H, Ghazal M, Sandhu HS, El-Baz A.
    Sensors (Basel); 2022 Mar 18; 22(6):. PubMed ID: 35336513
    [Abstract] [Full Text] [Related]

  • 14. Early diabetic retinopathy diagnosis based on local retinal blood vessel analysis in optical coherence tomography angiography (OCTA) images.
    Eladawi N, Elmogy M, Khalifa F, Ghazal M, Ghazi N, Aboelfetouh A, Riad A, Sandhu H, Schaal S, El-Baz A.
    Med Phys; 2018 Oct 18; 45(10):4582-4599. PubMed ID: 30144102
    [Abstract] [Full Text] [Related]

  • 15. The diagnostic value of optical coherence tomography angiography in diabetic retinopathy: a systematic review.
    Gildea D.
    Int Ophthalmol; 2019 Oct 18; 39(10):2413-2433. PubMed ID: 30382465
    [Abstract] [Full Text] [Related]

  • 16. 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 18; 26(5):2216-2227. PubMed ID: 34648460
    [Abstract] [Full Text] [Related]

  • 17. A computer-aided diagnostic system for detecting diabetic retinopathy in optical coherence tomography images.
    ElTanboly A, Ismail M, Shalaby A, Switala A, El-Baz A, Schaal S, Gimel'farb G, El-Azab M.
    Med Phys; 2017 Mar 18; 44(3):914-923. PubMed ID: 28035657
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  • 18. End-to-end diabetic retinopathy grading based on fundus fluorescein angiography images using deep learning.
    Gao Z, Jin K, Yan Y, Liu X, Shi Y, Ge Y, Pan X, Lu Y, Wu J, Wang Y, Ye J.
    Graefes Arch Clin Exp Ophthalmol; 2022 May 18; 260(5):1663-1673. PubMed ID: 35066704
    [Abstract] [Full Text] [Related]

  • 19. A Diabetic Retinopathy Classification Framework Based on Deep-Learning Analysis of OCT Angiography.
    Zang P, Hormel TT, Wang X, Tsuboi K, Huang D, Hwang TS, Jia Y.
    Transl Vis Sci Technol; 2022 Jul 08; 11(7):10. PubMed ID: 35822949
    [Abstract] [Full Text] [Related]

  • 20. A convolutional neural network for the screening and staging of diabetic retinopathy.
    Shaban M, Ogur Z, Mahmoud A, Switala A, Shalaby A, Abu Khalifeh H, Ghazal M, Fraiwan L, Giridharan G, Sandhu H, El-Baz AS.
    PLoS One; 2020 Jul 08; 15(6):e0233514. PubMed ID: 32569310
    [Abstract] [Full Text] [Related]

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