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arXiv · 2607.14179

OvAi Focus: AI-based Multi-class Segmentation of Functional Ovaries and Adnexal Masses in Gynecological Ultrasound

Niccolò Tallone·Francesca Salis·Pio Raffaele Fina·Roberta Massobrio·Rosilari Bellacosa Marotti·Daniele Conti·Luca Fuso·Luca Mariani·Annamaria Ferrero·Alessandro Arena·Stefano Cosma·Dan Grisaru·Angelo Lacalandra·Renato Seracchioli·Marianna Roccio·Federica Gerace
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Abstract

Ovarian cancer is the deadliest gynecological malignancy; accurate and objective segmentation of adnexal masses and functional ovaries in ultrasound (US) remains challenging due to operator variability and morphological complexity. We present OvAi Focus (SynDiag s.r.l., Italy), a stand-alone AI software medical device that performs multi-class semantic segmentation of functional ovaries and adnexal masses, distinguishing cystic from solid components. The system was trained and independently validated on a multicenter dataset of 1,081 adult women from 6 centers across Italy and Israel. Segmentation achieved DICE scores of 0.87 (complete lesion), 0.85 (cystic), 0.68 (solid), and 0.62 (functional ovary), in line with or superior to state-of-the-art approaches across heterogeneous acquisition settings.

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Niccolò Tallone, Francesca Salis, Pio Raffaele Fina, Roberta Massobrio, Rosilari Bellacosa Marotti, Daniele Conti, Luca Fuso, Luca Mariani, Annamaria Ferrero, Alessandro Arena, Stefano Cosma, Dan Grisaru, Angelo Lacalandra, Renato Seracchioli, Marianna Roccio, Federica Gerace. 2026-07-15. OvAi Focus: AI-based Multi-class Segmentation of Functional Ovaries and Adnexal Masses in Gynecological Ultrasound. https://arxiv.org/abs/2607.14179

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