Method of automatically detecting microaneurysm based on multi-sieving convolutional neural network
US10489909B2 · kind B2 · utility
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Key dates
| Filing date | Dec 1, 2017 |
| Grant date | Nov 26, 2019 |
| Priority date | — |
| Expiry date | May 21, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H15/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of automatically detecting microaneurysm based on multi-sieving convolutional neural network (CNN), includes the following steps of: A1), partitioning an image to be detected using random fern and obtaining an auxiliary channel image of the image according to a first partition result; and A2), inputting the auxiliary channel image obtained from step A1) and the image to a multi-sieving CNN training model to perform a detection and obtaining a microaneurysm detection result of the image. The process of establishing the training model includes: B1), using a current microaneurysm diagnostic report as samples and partitioning a lesion image in the microaneurysm diagnostic report using the random fern, and establishing the auxiliary channel image according to a second partition result; B2), comparing the obtained auxiliary channel image with a lesion-marked image of pixels, clarifying the samples according to a comparing result and performing the multi-sieving CNN training.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.