Enhancing repeatability of follicle counting with deep learning reconstruction high-resolution MRI in PCOS patients

Enhancing repeatability of follicle counting with deep learning reconstruction high-resolution MRI in PCOS patients

Abstract Follicle count, a pivotal metric in the adjunct diagnosis of polycystic ovary syndrome (PCOS), is often underestimated when assessed via transvaginal ultrasonography compared to MRI. Nevertheless, the repeatability of follicle counting using traditional MR images is still compromised by mot...

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Bibliographic Details
Main Authors: Renjie Yang, Yujie Zou, Liang Li, Weiyin Vivian Liu, Changsheng Liu, Zhi Wen, Yunfei Zha
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Ovary
Polycystic ovary syndrome
High resolution
Deep learning
Magnetic resonance imaging
Online Access:https://doi.org/10.1038/s41598-024-84812-3
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https://doi.org/10.1038/s41598-024-84812-3

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