AIMC Topic: Spermatozoa

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Deep learning-based method for analyzing the optically trapped sperm rotation.

Scientific reports
Optical tweezers exert a strong trapping force on cells, making it crucial to analyze the movement of trapped cells. The rotation of cells plays a significant role in their swimming patterns, such as in sperm cells. We proposed a fast deep-learning-b...

A Dual Architecture Fusion and AutoEncoder for Automatic Morphological Classification of Human Sperm.

Sensors (Basel, Switzerland)
Infertility has become a common problem in global health, and unsurprisingly, many couples need medical assistance to achieve reproduction. Many human behaviors can lead to infertility, which is none other than unhealthy sperm. The important thing is...

Improving outcomes of assisted reproductive technologies using artificial intelligence for sperm selection.

Fertility and sterility
Within the field of assisted reproductive technology, artificial intelligence has become an attractive tool for potentially improving success rates. Recently, artificial intelligence-based tools for sperm evaluation and selection during intracytoplas...

Structures of sperm flagellar doublet microtubules expand the genetic spectrum of male infertility.

Cell
Sperm motility is crucial for successful fertilization. Highly decorated doublet microtubules (DMTs) form the sperm tail skeleton, which propels the movement of spermatozoa. Using cryo-electron microscopy (cryo-EM) and artificial intelligence (AI)-ba...

Artificial intelligence for sperm selection-a systematic review.

Fertility and sterility
Despite the increasing number of assisted reproductive technologies based treatments being performed worldwide, there has been little improvement in fertilization and pregnancy outcomes. Male infertility is a major contributing factor, and sperm eval...

New horizons in human sperm selection for assisted reproduction.

Frontiers in endocrinology
Male infertility is a commonly encountered pathology that is estimated to be a contributory factor in approximately 50% of couples seeking recourse to assisted reproductive technologies. Upon clinical presentation, such males are commonly subjected t...

Sperm-cell DNA fragmentation prediction using label-free quantitative phase imaging and deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
In intracytoplasmic sperm injection (ICSI), a single sperm cell is selected and injected into an egg. The quality of the chosen sperm and specifically its DNA fragmentation have a significant effect on the fertilization success rate. However, there i...

Automated rare sperm identification from low-magnification microscopy images of dissociated microsurgical testicular sperm extraction samples using deep learning.

Fertility and sterility
OBJECTIVE: To develop a machine learning algorithm to detect rare human sperm in semen and microsurgical testicular sperm extraction (microTESE) samples using bright-field (BF) microscopy for nonobstructive azoospermia patients.

TOD-CNN: An effective convolutional neural network for tiny object detection in sperm videos.

Computers in biology and medicine
The detection of tiny objects in microscopic videos is a problematic point, especially in large-scale experiments. For tiny objects (such as sperms) in microscopic videos, current detection methods face challenges in fuzzy, irregular, and precise pos...

Reproductive characteristics of the giant gurami sago strain ( Lacepède, 1801): basic knowledge for a future hatchery development strategy.

F1000Research
The giant gourami sago strain ( Lacepède) has been approved in 2018 as a candidate for freshwater aquaculture in Indonesia. However, information on the species' reproduction is minimal. This study analyzed the reproductive characteristics of the go...