AIMC Topic: Adnexal Diseases
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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).
Exploratory study on the enhancement of O-RADS application effectiveness for novice ultrasonographers via deep learning.
Archives of gynecology and obstetrics
Nov 23, 2024
PURPOSE: The study aimed to create a deep convolutional neural network (DCNN) model based on ConvNeXt-Tiny to identify classic benign lesions (CBL) from other lesions (OL) within the Ovarian-Adnexal Reporting and Data System (O-RADS), enhancing the s...
Does she have adnexal torsion? Prediction of adnexal torsion in reproductive age women.
Archives of gynecology and obstetrics
Dec 21, 2017
PURPOSE: The aim of this study was to investigate the association of clinical, laboratory and ultrasound findings with the surgical diagnosis of adnexal torsion in a retrospective cohort of women operated for suspected torsion.
Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach.
Ultrasound in medicine & biology
Dec 20, 2015
The discrimination between benign and malignant adnexal masses in ultrasound images represents one of the most challenging problems in gynecologic practice. In the study described here, a new method for automatic discrimination of adnexal masses base...
Multimodal ultrasound-based radiomics and deep learning for differential diagnosis of O-RADS 4-5 adnexal masses.
Cancer imaging : the official publication of the International Cancer Imaging Society
May 23, 2025
BACKGROUND: Accurate differentiation between benign and malignant adnexal masses is crucial for patients to avoid unnecessary surgical interventions. Ultrasound (US) is the most widely utilized diagnostic and screening tool for gynecological diseases...
Accuracy of Large Language Model-based Automatic Calculation of Ovarian-Adnexal Reporting and Data System MRI Scores from Pelvic MRI Reports.
Radiology
Apr 1, 2025
Background Ovarian-Adnexal Reporting and Data System (O-RADS) for MRI helps assign malignancy risk, but radiologist adoption is inconsistent. Automatic assignment of O-RADS scores from reports could increase adoption and accuracy. Purpose To evaluate...
An explainable machine learning model to solid adnexal masses diagnosis based on clinical data and qualitative ultrasound indicators.
Cancer medicine
Jun 1, 2024
BACKGROUND: Accurate characterization of newly diagnosed a solid adnexal lesion is a key step in defining the most appropriate therapeutic approach. Despite guidance from the International Ovarian Tumor Analyzes Panel, the evaluation of these lesions...
Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: comparison with expert subjective assessment.
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Jan 1, 2021
OBJECTIVES: To develop and test the performance of computerized ultrasound image analysis using deep neural networks (DNNs) in discriminating between benign and malignant ovarian tumors and to compare its diagnostic accuracy with that of subjective a...
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