Automatic analysis of nuclear features reveals a non-tumoral predictor of tumor grade in bladder cancer

• Päätekijät: Ibrahim Fahoum (Tekijä), Shlomo Tsuriel (Tekijä), Daniel Rattner (Tekijä), Ariel Greenberg (Tekijä), Asia Zubkov (Tekijä), Rabab Naamneh (Tekijä), Orli Greenberg (Tekijä), Valentina Zemser-Werner (Tekijä), Gilad Gitstein (Tekijä), Rami Hagege (Tekijä), Dov Hershkovitz (Tekijä)
• Aineistotyyppi: Kirja
• Julkaistu: BMC, 2024-06-01T00:00:00Z.
• Aiheet: article
• Linkit: Connect to this object online.

Abstract Background & objectives Tumor grade determines prognosis in urothelial carcinoma. The classification of low and high grade is based on nuclear morphological features that include nuclear size, hyperchromasia and pleomorphism. These features are subjectively assessed by the pathologists...