RETINA VESSEL MEASUREMENT

Disclosed is a method for training a neural network to quantify the vessel calibre of retina fundus images. The method involves receiving a plurality of fundus images; pre-processing the fundus images to normalise images features of the fundus images; and training a multi-layer neural network, the n...

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Bibliographische Detailangaben
Hauptverfasser: HSU, Wynne, CHEUNG, Yim Lui, LEE, Mong Li, WONG, Tien Yin, XU, Dejiang
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:Disclosed is a method for training a neural network to quantify the vessel calibre of retina fundus images. The method involves receiving a plurality of fundus images; pre-processing the fundus images to normalise images features of the fundus images; and training a multi-layer neural network, the neural network comprising of a convolutional unit, multiple dense blocks alternating with transition units for down-sampling image features determined by the neural network, and a fully-connected unit, wherein each dense block comprises a series of cAdd units packed with multiple convolutions, and each transition layer comprises a convolution with pooling.