The Devil is in the Details: Whole Slide Image Acquisition and Processing for Artifacts Detection, Color Variation, and Data Augmentation: A Review Kanwal, Neel Pérez Bueno, Fernando Schmidt, Arne Molina Soriano, Rafael Artifacts detection Computational pathology Histopathological images Image augmentation Preprocessing Stain normalization Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis of different types of cancer. The preparation and digitization of histological tissues leads to the introduction of artifacts and variations that need to be addressed before the tissues are analyzed. WSI preprocessing can significantly improve the performance of computational pathology systems and is often used to facilitate human or machine analysis. Color preprocessing techniques are frequently mentioned in the literature, while other areas are usually ignored. In this paper, we present a detailed study of the state-of-the-art in three different areas of WSI preprocessing: Artifacts detection, color variation, and the emerging field of pathology-specific data augmentation. We include a summary of evaluation techniques along with a discussion of possible limitations and future research directions for new methods. 2022-07-04T10:21:34Z 2022-07-04T10:21:34Z 2022-05-18 info:eu-repo/semantics/article N. Kanwal... [et al.]. "The Devil is in the Details: Whole Slide Image Acquisition and Processing for Artifacts Detection, Color Variation, and Data Augmentation: A Review," in IEEE Access, vol. 10, pp. 58821-58844, 2022, doi: [10.1109/ACCESS.2022.3176091] http://hdl.handle.net/10481/75812 10.1109/ACCESS.2022.3176091 eng info:eu-repo/grantAgreement/EC/H2020/860627 http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional IEEE