An Intelligent Segmentation and Diagnosis Method for Diabetic Retinopathy Based on Improved U-NET Network

Due to insufficient samples, the generalization performance of deep network is insufficient. In order to solve this problem, an improved U-net based image automatic segmentation and diagnosis algorithm was proposed, in which the max-pooling operation in original U-net model was replaced by the convo...

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Veröffentlicht in:	Journal of medical systems Jg. 43; H. 9; S. 304 - 9
Hauptverfasser:	Li, Qianjin, Fan, Shanshan, Chen, Changsheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2019 Springer Nature B.V
Schlagworte:	Algorithms Convolution Deep learning Diabetes Diabetes mellitus Diabetic retinopathy Diabetic Retinopathy - diagnosis Diagnosis Distributed Analytics and Deep Learning in Health Care Feature extraction Health Informatics Health Sciences Humans Image & Signal Processing Image processing Image Processing, Computer-Assisted - methods Image segmentation Medical diagnosis Medicine Medicine & Public Health Neural Networks, Computer Retina - diagnostic imaging Retinopathy Sensitivity and Specificity Statistics for Life Sciences Training Deep learning Generalization performance Diabetic retinopathy Fully convolutional network U-net model Intelligent diagnosis
ISSN:	0148-5598, 1573-689X, 1573-689X
Online-Zugang:	Volltext
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