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...

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Bibliographic Details
Main Authors: Leifman, George (Contributor), Swedish, Tristan (Contributor), Roesch, Karin (Contributor), Raskar, Ramesh (Contributor)
Other Authors: Massachusetts Institute of Technology. Media Laboratory (Contributor), Program in Media Arts and Sciences (Massachusetts Institute of Technology) (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2017-07-07T20:35:57Z.
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