GIUSEPPINA BONIZZI, LORENZO ZATTONI, NICOLA FUSCO^*

Oncology Research, Vol.29, No.4, pp. 229-233, 2021, DOI:10.32604/or.2022.024892

Abstract Digital Pathology is becoming more and more important to achieve the goal of precision medicine. Advances in whole-slide imaging, software integration, and the accessibility of storage solutions have changed the pathologists’ clinical practice, not only in terms of laboratory workflow but also for diagnosis and biomarkers analysis. In parallel with the pathology setting advancement, translational medicine is approaching the unprecedented opportunities unrevealed by artificial intelligence (AI). Indeed, the increased usage of biobanks’ datasets in research provided new challenges for AI applications, such as advanced algorithms, and computer-aided techniques. In this scenario, machine learning-based approaches are being propose in order to… More >

Afzan Adam^1,*, Abdul Hadi Abd Rahman¹, Nor Samsiah Sani¹, Zaid Abdi Alkareem Alyessari¹, Nur Jumaadzan Zaleha Mamat², Basela Hasan³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 761-777, 2021, DOI:10.32604/cmc.2021.014599

Abstract Boundary effect in digital pathology is a phenomenon where the tissue shapes of biopsy samples get distorted during the sampling process. The morphological pattern of an epithelial layer is greatly affected. Theoretically, the shape deformation model can normalise the distortions, but it needs a 2D image. Curvatures theory, on the other hand, is not yet tested on digital pathology images. Therefore, this work proposed a curvature detection to reduce the boundary effects and estimates the epithelial layer. The boundary effect on the tissue surfaces is normalised using the frequency of a curve deviates from being a straight line. The epithelial… More >