Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images

Understand

Tissue segmentation is an important pre-requisite for efficient and accurate diagnostics in digital pathology.

• However, it is well known that whole-slide scanners can fail in detecting all tissue regions, for example due to the tissue type, or due to weak staining because their tissue detection algorithms are not robust enough.
• In this paper, we introduce two different convolutional neural network architectures for whole slide image segmentation to accurately identify the tissue sections.
• We also compare the algorithms to a published traditional method.