Riccardo Gambino
Pattern recognition methods for detection of ovarian cysts papillary projections in sonographic videos.
Rel. Filippo Molinari, Daniele Conti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2021
Abstract
Ovarian cancer is one of the leading causes of tumor related deaths in women and it has the highest mortality rate among gynecological cancer diseases. The reason why this type of cancer is among the deadliest ones is due to the fact that the absence of specific symptoms leads to a delay in diagnosis. Moreover, ovarian cancer diagnosis is often performed with sonography (ultrasound, US), which is considered the gold standard examination, but shows high user-dependance. Finding a way to get an early diagnosis is fundamental to drastically reduce mortality. According to the international guidelines adopted by the medical community, the presence of papillary projections within ovarian cysts is a discriminant feature between benign and malignant conditions.
However, the detection of the papillary projections in US videos is a complex task and affected by variability in observer interpretation
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