Deep Bayesian baseline for segmenting diabetic retinopathy lesions: Advances and challenges

Early diagnosis of retinopathy is essential for preventing retinal complications and visual impairment due to diabetes. For the detection of retinopathy lesions from retinal images, several automatic approaches based on deep neural networks have been developed in the recent years. Most of the propos...

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Veröffentlicht in:	Computers in biology and medicine 2021-09, Vol.136, p.104725-104725, Article 104725
Hauptverfasser:	Garifullin, Azat, Lensu, Lasse, Uusitalo, Hannu
Format:	Artikel
Sprache:	eng
Schlagworte:	Abnormalities Algorithms Artificial neural networks Bayesian analysis Bayesian deep learning Calibration Complications Datasets Deep learning Diabetes Diabetes mellitus Diabetic retinopathy Exudates Exudation Haemorrhage Hard exudate Hemorrhage Image segmentation Lesion segmentation Lesions Microaneurysm Neural networks Probabilistic models Probability Production methods Random variables Retina Retinal images Retinopathy Soft exudate Training Uncertainty
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