  Breast cancer is one of the most common and deadliest cancers among women.
Since histopathological images contain sufficient phenotypic information, they
play an indispensable role in the diagnosis and treatment of breast cancers. To
improve the accuracy and objectivity of Breast Histopathological Image Analysis
(BHIA), Artificial Neural Network (ANN) approaches are widely used in the
segmentation and classification tasks of breast histopathological images. In
this review, we present a comprehensive overview of the BHIA techniques based
on ANNs. First of all, we categorize the BHIA systems into classical and deep
neural networks for in-depth investigation. Then, the relevant studies based on
BHIA systems are presented. After that, we analyze the existing models to
discover the most suitable algorithms. Finally, publicly accessible datasets,
along with their download links, are provided for the convenience of future
researchers.
