par Foucart, Adrien 
;Elskens, Arthur ;Debeir, Olivier ;Decaestecker, Christine
Référence SIPAIM(15-17/11/2023: Mexico City, Mexico), Proceedings of the 19th International Symposium on Medical Information Processing and Analysis
Publication Publié, 2024-01-01
;Elskens, Arthur ;Debeir, Olivier ;Decaestecker, Christine Référence SIPAIM(15-17/11/2023: Mexico City, Mexico), Proceedings of the 19th International Symposium on Medical Information Processing and Analysis
Publication Publié, 2024-01-01
Publication dans des actes
| Résumé : | In digital pathology, segmentation between tissue and glass slide is a very common pre-processing step in image processing pipelines. It is often presented as relatively trivial, and solved using ad-hoc heuristics that are not always precisely defined nor justified. Most tissue segmentation pipelines start by reducing the color image to a single-channel representation, grayscale being the most common. We show in this study that representations that focus on the colorfulness or entropy offer better separability between tissue and background, and lead to better results in simple thresholding pipelines. |
