AIMC Topic: Ovary
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A Multi-Modal Pelvic MRI Dataset for Deep Learning-Based Pelvic Organ Segmentation in Endometriosis.
Scientific data
Jul 24, 2025
Endometriosis affects approximately 190 million females of reproductive age worldwide. Magnetic Resonance Imaging (MRI) has been recommended as the primary non-invasive diagnostic method for endometriosis. This study presents new female pelvic MRI mu...
Assessment and prediction models for the quantitative and qualitative reserve of the ovary using machine learning.
Journal of ovarian research
Jul 18, 2025
BACKGROUND: The age-related decline of fertility is caused by a reduction of the ovarian reserve, which is represented by the number and quality of oocytes in the ovaries. Anti-Müllerian hormone (AMH) is considered one of the most useful markers of t...
Automated high precision PCOS detection through a segment anything model on super resolution ultrasound ovary images.
Scientific reports
May 15, 2025
PCOS (Poly-Cystic Ovary Syndrome) is a multifaceted disorder that often affects the ovarian morphology of women of their reproductive age, resulting in the development of numerous cysts on the ovaries. Ultrasound imaging typically diagnoses PCOS, whi...
Intra- and interobserver agreement of proposed objective transvaginal ultrasound image-quality scoring system for use in artificial intelligence algorithm development.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Jan 24, 2025
OBJECTIVES: The development of valuable artificial intelligence (AI) tools to assist with ultrasound diagnosis depends on algorithms developed using high-quality data. This study aimed to test the intra- and interobserver agreement of a proposed imag...
A Study on Automatic O-RADS Classification of Sonograms of Ovarian Adnexal Lesions Based on Deep Convolutional Neural Networks.
Ultrasound in medicine & biology
Nov 26, 2024
OBJECTIVE: This study explored a new method for automatic O-RADS classification of sonograms based on a deep convolutional neural network (DCNN).
Application of convolutional neural network for differentiating ovarian thecoma-fibroma and solid ovarian cancer based on MRI.
Acta radiologica (Stockholm, Sweden : 1987)
May 15, 2024
BACKGROUND: Ovarian thecoma-fibroma and solid ovarian cancer have similar clinical and imaging features, and it is difficult for radiologists to differentiate them. Since the treatment and prognosis of them are different, accurate characterization is...
Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis.
Clinical radiology
Mar 15, 2024
AIM: The objective of this study is to explore the diagnostic value of machine learning (ML) in borderline ovarian tumors through meta-analysis.
Automated Measurement of Ovary Development in Atlantic Salmon Using Deep Learning.
Ultrasound in medicine & biology
Jan 8, 2024
OBJECTIVE: Salmon breeding companies control the egg stripping period through environmental change, which triggers the need to identify the state of maturation. Ultrasound imaging of the salmon ovary is a proven non-invasive tool for this purpose; ho...
An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries.
Development (Cambridge, England)
Apr 3, 2023
Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms a...
Development of MRI-Based Radiomics Model to Predict the Risk of Recurrence in Patients With Advanced High-Grade Serous Ovarian Carcinoma.
AJR. American journal of roentgenology
Jul 14, 2021
The purpose of our study was to develop a radiomics model based on preoperative MRI and clinical information for predicting recurrence-free survival (RFS) in patients with advanced high-grade serous ovarian carcinoma (HGSOC). This retrospective stu...
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