Leveraging the crowd for annotation of retinal images
Medical data presents a number of challenges. It tends to be unstructured, noisy and protected. To train algorithms to understand medical images, doctors can label the condition associated with a particular image, but obtaining enough labels can be difficult. We propose an annotation approach which...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2017
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| Online Access: | http://hdl.handle.net/1721.1/110565 https://orcid.org/0000-0001-5574-0311 https://orcid.org/0000-0002-5453-6121 https://orcid.org/0000-0002-3254-3224 |