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For: Karimi D, Dou H, Warfield SK, Gholipour A. Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis. Med Image Anal 2020;65:101759. [PMID: 32623277 DOI: 10.1016/j.media.2020.101759] [Cited by in Crossref: 46] [Cited by in F6Publishing: 25] [Article Influence: 23.0] [Reference Citation Analysis]
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22 Gehlot S, Gupta A, Gupta R. A CNN-based unified framework utilizing projection loss in unison with label noise handling for multiple Myeloma cancer diagnosis. Med Image Anal 2021;72:102099. [PMID: 34098240 DOI: 10.1016/j.media.2021.102099] [Reference Citation Analysis]
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26 Yousefirizi F, Pierre Decazes, Amyar A, Ruan S, Saboury B, Rahmim A. AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging:: Towards Radiophenomics. PET Clin 2022;17:183-212. [PMID: 34809866 DOI: 10.1016/j.cpet.2021.09.010] [Reference Citation Analysis]
27 Mordhorst L, Morozova M, Papazoglou S, Fricke B, Oeschger JM, Tabarin T, Rusch H, Jäger C, Geyer S, Weiskopf N, Morawski M, Mohammadi S. Towards a representative reference for MRI-based human axon radius assessment using light microscopy. Neuroimage 2022;:118906. [PMID: 35032659 DOI: 10.1016/j.neuroimage.2022.118906] [Reference Citation Analysis]
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30 Wood DA, Kafiabadi S, Busaidi AA, Guilhem E, Montvila A, Lynch J, Townend M, Agarwal S, Mazumder A, Barker GJ, Ourselin S, Cole JH, Booth TC. Deep learning models for triaging hospital head MRI examinations. Medical Image Analysis 2022. [DOI: 10.1016/j.media.2022.102391] [Reference Citation Analysis]
31 Martins R, Oliveira F, Moreira F, Moreira AP, Abrunhosa A, Januário C, Castelo-Branco M. Automatic classification of idiopathic Parkinson's disease and atypical Parkinsonian syndromes combining [11C]raclopride PET uptake and MRI grey matter morphometry. J Neural Eng 2021;18. [PMID: 33848996 DOI: 10.1088/1741-2552/abf772] [Reference Citation Analysis]
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36 Tang C, Uriarte M, Jin H, Morton D, Zheng T, Ellison A. Large‐scale, image‐based tree species mapping in a tropical forest using artificial perceptual learning. Methods Ecol Evol 2021;12:608-18. [DOI: 10.1111/2041-210x.13549] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
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39 Schmarje L, Brünger J, Santarossa M, Schröder SM, Kiko R, Koch R. Fuzzy Overclustering: Semi-Supervised Classification of Fuzzy Labels with Overclustering and Inverse Cross-Entropy. Sensors (Basel) 2021;21:6661. [PMID: 34640981 DOI: 10.3390/s21196661] [Reference Citation Analysis]
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44 Karimi D, Peters JM, Ouaalam A, Prabhu SP, Sahin M, Krueger DA, Kolevzon A, Eng C, Warfield SK, Gholipour A. LEARNING TO DETECT BRAIN LESIONS FROM NOISY ANNOTATIONS. Proc IEEE Int Symp Biomed Imaging 2020;2020:1910-4. [PMID: 32879655 DOI: 10.1109/isbi45749.2020.9098599] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
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