ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

ABSTRACT: Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely accurate and, ideally, provide a measure of uncertainty for its predictions. Such accurate and reliable classifiers need enough labelled data for training, which requires time-consuming and costly manual annotation by pathologists. Thus, it is critical to minimise the amount of data needed to reach the desired accuracy by maximising the efficiency of training. We propose an accurate, reliable and active (ARA) image classification framework and introduce a new Bayesian Convolutional Neural Network (ARA-CNN) for classifying histopathological image

SUBMITTER: Raczkowska A 

PROVIDER: S-EPMC6778075 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature