AIMC Topic: Ovary

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Contrastive rendering with semi-supervised learning for ovary and follicle segmentation from 3D ultrasound.

Medical image analysis
Segmentation of ovary and follicles from 3D ultrasound (US) is the crucial technique of measurement tools for female infertility diagnosis. Since manual segmentation is time-consuming and operator-dependent, an accurate and fast segmentation method i...

A Transfer Learning Based Super-Resolution Microscopy for Biopsy Slice Images: The Joint Methods Perspective.

IEEE/ACM transactions on computational biology and bioinformatics
Higher-resolution biopsy slice images reveal many details, which are widely used in medical practice. However, taking high-resolution slice images is more costly than taking low-resolution ones. In this paper, we propose a joint framework containing ...

Ovarian torsion: developing a machine-learned algorithm for diagnosis.

Pediatric radiology
BACKGROUND: Ovarian torsion is a common concern in girls presenting to emergency care with pelvic or abdominal pain. The diagnosis is challenging to make accurately and quickly, relying on a combination of physical exam, history and radiologic evalua...

CR-Unet: A Composite Network for Ovary and Follicle Segmentation in Ultrasound Images.

IEEE journal of biomedical and health informatics
Transvaginal ultrasound (TVUS) is widely used in infertility treatment. The size and shape of the ovary and follicles must be measured manually for assessing their physiological status by sonographers. However, this process is extremely time-consumin...

Caloric restriction and IGF-I administration promote rabbit fecundity: Possible interrelationships and mechanisms of action.

Theriogenology
The aim of these in vivo and in vitro studies was to examine the influence of caloric restriction (CR), and the administration of insulin-like growth factor (IGF-I), on rabbit fecundity and to understand the interrelationships between CR and IGF-I, a...

Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.

PloS one
Medical diagnostics is often a multi-attribute problem, necessitating sophisticated tools for analyzing high-dimensional biomedical data. Mining this data often results in two crucial bottlenecks: 1) high dimensionality of features used to represent ...

Associated Da Vinci and magellan robotic systems for successful treatment of nutcracker syndrome.

Journal of laparoendoscopic & advanced surgical techniques. Part A
Here, we report the case of a 26-year-old woman suffering from nutcracker syndrome with concurrent disabling pelvic congestion syndrome. She was given the minimally invasive treatment of left renal vein transposition with the Da Vinci(®) robotic syst...

Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models.

BMC medicine
BACKGROUND: Polycystic ovary syndrome (PCOS) is a common reproductive and metabolic disorder in the reproductive-age women. The international evidence-based guideline for the assessment and management of PCOS 2023 now suggests raising the follicle nu...

Accuracy of Large Language Model-based Automatic Calculation of Ovarian-Adnexal Reporting and Data System MRI Scores from Pelvic MRI Reports.

Radiology
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...