Dario Fenoglio
Deep learning method for prostate cancer segmentation and quantification in immunohistochemical staining.
Rel. Massimo Salvi, Filippo Molinari. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2022
Abstract
The prostate is formed of different types of cells, and each of them can mutate and become cancerous. Prostate cancer (PCa), the most common male neoplasia, is estimated to affect about 36,074 people in Italy every year, according to 2020’s statistics. Recent studies show how 1 fifty years old man out of 4 has PCa cells, whereas at the age of eighty this condition affects 1 out of 2. Although widespread, PCa does not always present as an aggressive form, but commonly manifests itself in a benign form, such as prostatic hyperplasia. Therefore, it is essential to estimate the correct tumor grade (i.e., Gleason Score) because it is directly related to the intervention strategy adopted which can range from radiotherapy and radical prostatectomy to active surveillance in a slow tumor growth case.
Nowadays, the PCa diagnosis is performed manually by the pathologist through a histological analysis in H&E of prostate tissue removed through agobiopsy from the patient
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