TCNN: A Transformer Convolutional Neural Network for Artifact Classification in Whole Slide Images
The TCNN project aims to automate the detection of artifacts in pathological images. By treating artifact detection as a binary classification task, TCNN offers a solution to identify unwanted patterns that may arise during slide processing. This method reduces the need for manual labeling by laboratory technicians, thereby minimizing the risk of erroneous data being analyzed by pathologists and physicians. Unidentified artifact patches can compromise the accuracy of Computer-Aided Diagnosis (CAD) systems.
