Negative Evidence Matters in Interpretable Histology Image Classification. (arXiv:2201.02445v1 [eess.IV])

Using only global annotations such as the image class labels,
weakly-supervised learning methods allow CNN classifiers to jointly classify an
image, and yield the regions of interest associated with the predicted class.
However, without any guidance at the pixel level, such methods may yield
inaccurate regions. This problem is known to be more challenging with histology
images than with natural ones, since objects are less salient, structures have
more variations, and foreground and background regions have stronger
similarities. Therefore, methods …

arxiv classification negative