Abstract
Seattle protocol biopsies for Barrett’s esophagus (BE) surveillance are labour intensive with low compliance and limited accuracy for detecting dysplasia. Dysplasia detection rates (DDR) vary significantly and lead to under diagnosis. This can potentially be offset with computer aided diagnosis. We aim to develop a deep neural network to aid the diagnosis and localisation of BE dysplasia with targeted biopsies.
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