# OvAi Focus: AI-based Multi-class Segmentation of Functional Ovaries and Adnexal Masses in Gynecological Ultrasound Source: [OvAi Focus: AI-based Multi-class Segmentation of Functional Ovaries and Adnexal Masses in Gynecological Ultrasound]() Collection index: [llms.txt]() Data updated: 2026-07-18T05:00:05.624Z Authors: Niccol\\\`o 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 Published: 2026-07-15T13:58:13.000Z ## 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. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()