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Ovarian Follicle

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Deep Learning based Quantification of Ovary and Follicles using 3D Transvaginal Ultrasound in Assisted Reproduction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Quantification of ovarian and follicular volume and follicle count are performed in clinical practice for diagnosis and management in assisted reproduction. Ovarian volume and Antral Follicle Count (AFC) are typically tracked over the ovulation cycle...

Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure.

Proceedings of the National Academy of Sciences of the United States of America
The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrin...

A Workflow for the Performance of the Differential Ovarian Follicle Count Using Deep Neuronal Networks.

Toxicologic pathology
In order to automate the counting of ovarian follicles required in multigeneration reproductive studies performed in the rat according to Organization for Economic Co-operation and Development guidelines 443 and 416, the application of deep neural ne...

F-Net: Follicles Net an efficient tool for the diagnosis of polycystic ovarian syndrome using deep learning techniques.

PloS one
The study's primary objectives encompass the following: (i) To implement the object detection of ovarian follicles using you only look once (YOLO)v8 and subsequently segment the identified follicles using a hybrid fuzzy c-means-based active contour t...

Quantification of follicles in human ovarian tissue using image processing software and trained artificial intelligence†.

Biology of reproduction
Cancer survival rates in prepubertal girls and young women have risen in recent decades due to increasingly efficient treatments. However, many such treatments are gonadotoxic, causing premature ovarian insufficiency, loss of fertility, and ovarian e...

Automatic ovarian follicle detection using object detection models.

Scientific reports
Ovaries are of paramount importance in reproduction as they produce female gametes through a complex developmental process known as folliculogenesis. In the prospect of better understanding the mechanisms of folliculogenesis and of developing novel p...

Explainable artificial intelligence to identify follicles that optimize clinical outcomes during assisted conception.

Nature communications
Infertility affects one-in-six couples, often necessitating in vitro fertilization treatment (IVF). IVF generates complex data, which can challenge the utilization of the full richness of data during decision-making, leading to reliance on simple 'ru...

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

Scientific reports
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 traditio...

Interpretable Artificial Intelligence for Analysing Changes in Gases in the Uterine Environment of Cows According to Physiological Structures in the Ovary.

Veterinary medicine and science
The objective of the present study was to examine the relationship between the gases in a cow's uterine environment and its ovarian physiological structures using the sunflower optimisation algorithm (SFOA) deployed in a device called Metrisör, devel...