AIMC Topic: Microdissection
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Artificial intelligence interpretation of touch print smear cytology of testicular specimen from patients with azoospermia.
Journal of assisted reproduction and genetics
Sep 3, 2024
PURPOSE: Identification of mature sperm at microdissection testicular sperm extraction (mTESE) is a crucial step of sperm retrieval to help patients with non-obstructive azoospermia (NOA) proceed to intracytoplasmic sperm injection. Touch print smear...
Development of a deep-learning model for detecting positive tubules during sperm recovery for nonobstructive azoospermia.
Reproduction (Cambridge, England)
Aug 27, 2024
To enhance surgical testicular sperm retrieval outcome for men with nonobstructive azoospermia, a deep-learning model was developed to identify positive seminiferous tubules by labeling 110 images with sperm-containing tubules sampled during microdis...
Deep learning-based real-time detection of neurons in brain slices for in vitro physiology.
Scientific reports
Mar 16, 2021
A common electrophysiology technique used in neuroscience is patch clamp: a method in which a glass pipette electrode facilitates single cell electrical recordings from neurons. Typically, patch clamp is done manually in which an electrophysiologist ...
A preliminary study of sperm identification in microdissection testicular sperm extraction samples with deep convolutional neural networks.
Asian journal of andrology
Jan 1, 2021
Sperm identification and selection is an essential task when processing human testicular samples for in vitro fertilization. Locating and identifying sperm cell(s) in human testicular biopsy samples is labor intensive and time consuming. We developed...
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