AIMC Topic: Uterus

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DCS-NET: a multi-task model for uterine ROI detection and automatic staging of early endometrial cancer in MRI.

Scientific reports
Endometrial cancer (EC) is the most common gynecologic malignancy, with a steadily increasing incidence worldwide. Abnormal vaginal bleeding, a hallmark symptom, enables early diagnosis, which is critical for improving clinical outcomes. Pelvic magne...

Prediction of uterine cavity conception environment using two-dimensional transvaginal ultrasound imaging semantic feature-based machine learning: a case-control study.

BMC pregnancy and childbirth
BACKGROUND: Independently investigating the association between pregnancy outcomes and the uterine cavity conception environment (UCCE) is challenging. Therefore, this study aimed to employ a range of machine learning algorithms to systematically ana...

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
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...

Improved Image Quality Through Deep Learning Acceleration of Gradient-Echo Acquisitions in Uterine MRI: First Application with the Female Pelvis.

Academic radiology
RATIONALE AND OBJECTIVES: The aim of this study was to compare the image quality of a deep learning (DL)-accelerated volumetric interpolated breath-hold examination (VIBE) sequence with a standard (ST) VIBE sequence in assessing the uterus.

Recurrent pregnancy loss: risk factors and predictive modeling approaches.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
PURPOSE: This review aims to identify and analyze the risk factors associated with recurrent pregnancy loss (RPL) and to evaluate the effectiveness of various predictive models in estimating the risk of RPL. The review also explores recent advancemen...

Development and validation of a deep learning-based method for automatic measurement of uterus, fibroid, and ablated volume in MRI after MR-HIFU treatment of uterine fibroids.

European journal of radiology
INTRODUCTION: The non-perfused volume divided by total fibroid load (NPV/TFL) is a predictive outcome parameter for MRI-guided high-intensity focused ultrasound (MR-HIFU) treatments of uterine fibroids, which is related to long-term symptom relief. I...

Metrisor: A novel diagnostic method for metritis detection in cattle based on machine learning and sensors.

Theriogenology
The Metrisor device has been developed using gas sensors for rapid, highly accurate and effective diagnosis of metritis. 513 cattle uteri were collected from abattoirs and swabs were taken for microbiological testing. The Metrisor device was used to ...

A lightweight hybrid model for the automatic recognition of uterine fibroid ultrasound images based on deep learning.

Journal of clinical ultrasound : JCU
PURPOSE: Uterine fibroids (UF) are the most frequent tumors in ladies and can pose an enormous threat to complications, such as miscarriage. The accuracy of prognosis may also be affected by way of doctor inexperience and fatigue, underscoring the wa...

What is the impact of intraperitoneal surfactant administration against postoperative intraabdominal adhesion formation? an experimental study.

Turkish journal of medical sciences
BACKGROUND/AIM: Surfactant is a surface-active substance that, in addition to its detergent effect, also has effects that reduce inflammation and fibrosis. Because of these effects, it was aimed herein to investigate the effect of intraperitoneal sur...