Roberta Patti
Development of a deep learning-based method for artifact detection and quality controls in digital pathology.
Rel. Massimo Salvi, Filippo Molinari. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2022
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Abstract
In the last years, in an attempt to overcome some of the issues of traditional pathology, whole slide digital scanners have been adopted, enabling the transition of pathology into the digital era. Histological slides can now be digitalized, but the process that goes from the collection of the tissue to the digital image consists of specific sequential steps, typically carried out manually by laboratory technicians, each of which can introduce artifacts such as tissue folds, air bubble, pen marker or dust, that can lower the quality of the histological image. These artifacts may alter the appearance of the tissue, making diagnosis difficult for the pathologist and negatively affecting the performance of automatic algorithms that operate on digital WSI.
For these reasons, a quality control mechanism is needed
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