Classification of Mammographic Breast Microcalcifications Using a Deep Convolutional Neural Network: A BI-RADS–Based Approach

Conclusions

The dCNNs can be trained to successfully classify microcalcifications on mammograms according to the BI-RADS classification system in order to act as a standardized quality control tool providing the expertise of a team of radiologists.

The goal of this retrospective cohort study was to investigate the potential of a deep convolutional neural network (dCNN) to accurately classify microcalcifications in mammograms with the aim of obtaining a standardized observer-independent microcalcification classification system based on the Breast Imaging Reporting and Data System (BI-RADS) catalog.

Source: Investigative Radiology - March 10, 2021 Category: Radiology Tags: Original Articles Source Type: research