Input
A sperm image or video is analysed by a digital system.
Technologies · Image Analysis and Decision Support
AI-Assisted Sperm Selection Treatment
AI-assisted sperm selection refers to emerging technologies designed to analyse motility, morphology and other visible features in microscopic images using algorithms, providing decision support to the embryologist.
- Technology should be used under human supervision
- Model performance should be validated with the laboratory's own data
- An algorithm score is not a guarantee of pregnancy or a healthy child
Understand the topic in 1 minute
AI-Assisted Sperm Selection at a Glance
Analysis
Motility, shape, track and some visible characteristics may be classified algorithmically.
Decision support
The system may provide the embryologist with candidate-cell rankings or quality scores.
Limit
Outcomes such as DNA integrity and live birth cannot be determined with certainty from an image.
Essential information
What Is AI-Assisted Sperm Selection?
The term covers different devices and software platforms; it is not one standardised method.
Short answer:
A camera and image-processing system tracks, measures or classifies sperm cells. The final clinical decision is made by the trained embryologist and treatment team.
AI is being studied for tasks such as sperm counting, motility tracking, morphology classification and ranking candidate cells for ICSI according to image features.
Good performance on an algorithm's development dataset does not mean it will produce the same result with a different microscope, camera, patient group or laboratory. External validation and prospective clinical studies are required.
Image-based systems do not directly see sperm DNA integrity, chromosome structure or future embryo development. Algorithm output should therefore not be presented as a definitive label of biological quality.
- The clinical purpose of the system is clearly defined
- Data privacy and patient consent are protected
- The embryologist makes the final decision
- Guarantee language is avoided unless a live-birth benefit has been demonstrated
Method comparison
AI-Assisted vs Manual Sperm Selection
The two approaches are not necessarily alternatives; in suitable systems they may complement each other.
Embryologist Selection
Motility, appearance and procedural suitability are assessed under the microscope.
- Interprets the clinical context
- Adapts to unexpected situations
- Observer variability may occur
AI Analysis
Performs measurement and classification on digital images.
- Aims for repeatable measurement
- Can screen large numbers of cells
- May be affected by model bias and validation limitations
What is the safest approach?
Use a human-supervised decision-support model that has been validated in the laboratory and whose outcomes are monitored.
Who may be considered?
When Can AI-Assisted Sperm Selection Be Used?
Use depends on the device's approved purpose and the laboratory's validation.
Digital semen analysis
Image analysis supporting sperm count and motility measurement.
Morphology classification
Supporting a standardised assessment of sperm shape.
ICSI decision support
Ranking a large number of candidate cells according to image characteristics.
Quality control
Monitoring observer variability and supporting training.
Research
Studying relationships between image characteristics, DNA damage and embryo outcomes.
Human-supervised use
When final selection is confirmed by the embryologist.
Is it routinely necessary for everyone?
No. Routine use of systems without demonstrated clinical benefit or live-birth advantage should be justified carefully.
Assessment and preparation
What Should Be Checked in an AI System?
Technical and clinical validation are required before the technology is used.
Device and software version
The exact model version in use is documented.
Camera standard
Magnification, lighting and image quality are standardised.
Local validation
Model performance is checked using the laboratory's own samples.
Human comparison
Algorithm output is compared with assessment by experienced embryologists.
Data security
Access rules for images and patient data are defined.
Outcome monitoring
Fertilisation, embryo development and clinical outcomes are monitored.
Step-by-step process
How Does AI-Assisted Sperm Selection Work?
Although systems differ, the general workflow consists of image capture, analysis and human verification.
Sample preparation
Sperm cells are prepared using an appropriate laboratory method.
Image capture
A microscope camera records photographs or video.
Cell detection
The algorithm separates sperm cells from the background.
Motility tracking
If video is used, cell trajectories and speeds are calculated.
Morphology analysis
Visible head, midpiece and tail characteristics are classified.
Scoring
The system may assign probability or quality scores to candidate cells.
Embryologist review
Suitability and viability are confirmed by a person.
Documentation and outcome monitoring
Algorithm outputs and clinical outcomes are retained within the quality system.
Timeline
How Long Does AI-Assisted Sperm Selection Take?
Analysis is integrated into the laboratory workflow and does not create a separate treatment day.
Sample preparation
Standard sperm preparation is completed.
Imaging
Images are recorded rapidly through the camera and software.
Algorithm analysis
Depending on the system, this may take seconds or minutes.
Human verification
The embryologist reassesses the candidate cells.
ICSI
The selected sperm can be used on the same day.
Quality record
Data and outcome monitoring are added to the system.
How many days do I need to stay in Cyprus?
No additional travel or stay is required; it is part of the IVF/ICSI laboratory process.
Factors affecting results
What Affects the Performance of an AI System?
Algorithmic accuracy and clinical benefit are not the same thing.
Training data
A model may perform well only on data similar to the examples it has seen.
Microscope and camera
Performance may fall when imaging hardware changes.
Label quality
The expert labels used during training define the model's limits.
Patient diversity
Different sperm abnormalities and sample types affect generalisability.
External validation
Independent testing at other centres is required.
Clinical endpoint
Validation against fertilisation, pregnancy and live-birth data is important.
Important distinction:
Correctly classifying a sperm cell does not mean an algorithm increases the live-birth rate.
Personal cost planning
Cost of AI-Assisted Sperm Selection
Technology costs vary according to the software, device, licence and laboratory-use model.
Software licence
System or annual-use licence.
Imaging hardware
Camera, microscope integration and workstation.
Validation
Local testing and quality-control studies.
Laboratory time
Imaging and human verification.
ICSI
The technology is most often added to the ICSI process.
Data security
Storage, access and maintenance requirements.
Learn about your personal plan
We can assess the clinical purpose of the system, the level of evidence and whether it adds meaningful cost in your case.
Laboratory and traceability01 02 03 04 05 06
Validation and Traceability in AI Systems
Algorithm output should be linked within the laboratory quality system to the device, software version, operator and patient record.
Version record
A software update may change performance.
Calibration
Microscope, camera and imaging conditions are standardised.
Human supervision
The embryologist is responsible for the final decision and management of exceptions.
Performance monitoring
Misclassification and clinical outcomes are tracked.
Data privacy
Images are stored in a secure, authorised system.
Transparent consent
The purpose of the technology and the limits of the evidence are explained to the patient.
Multidisciplinary approach
AI-Assisted Sperm Assessment Team
Technology decisions are a shared responsibility of the clinician, scientific leadership and embryology laboratory.
Obstetrics, Gynaecology and IVF Specialist
Op. Dr. Beril Yüksel
Assesses the clinical contribution of the technology to the couple's treatment plan.
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Scientific Director
Prof. Dr. Münevver Serdaroğulları
Oversees the framework for evidence, ethics, consent and quality management.
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Embryology Laboratory Director
Zafer Atayurt
Manages imaging, algorithm output, human verification and ICSI implementation.
View profile →Urology and andrology assessment
AI does not replace the urological diagnosis of male infertility or hormonal and genetic assessment.
Balanced information
Risks and Limitations of AI-Assisted Sperm Selection
Algorithmic systems involve biological and technical uncertainty.
Model bias
Training data may not adequately represent certain patient groups.
Generalisability
Performance at one centre may not transfer to another laboratory.
False reassurance
A high score is not a guarantee of healthy DNA or live birth.
Version changes
Software updates can change results.
Data privacy
Patient images and data must be protected.
Unnecessary cost
It may create an additional routine charge before clinical benefit has been established.
Questions patients ask
Frequently Asked Questions About AI-Assisted Sperm Selection
Real-world uses and evidence limitations of an emerging technology.
What is AI-assisted sperm selection?
These systems analyse sperm images with algorithms to provide measurement or ranking support to the embryologist.
Does AI find the healthiest sperm?
It analyses visible image features; it cannot determine DNA or genetic health with certainty.
Does AI replace the embryologist?
No. The final decision and procedure should remain under human supervision.
Does AI increase the chance of pregnancy?
For many systems, a live-birth advantage has not yet been demonstrated sufficiently.
Can AI see sperm DNA damage?
DNA breaks cannot be seen directly in standard images; some research models attempt to predict them.
Can AI perform sperm counting?
Some digital systems can analyse sperm count and motility.
Is AI used in ICSI?
It may be used as decision support when ranking candidate sperm cells.
Does every laboratory use the same AI system?
No. Devices, models and software versions differ.
How is an algorithm result validated?
Local laboratory validation, human comparison and clinical outcome monitoring are required.
Are patient data secure in an AI system?
The system's data-storage, access and anonymisation policies should be explained.
Does AI involve an additional fee?
There may be an additional cost depending on the system; the clinical benefit should be explained clearly.
Do I need an additional stay in Cyprus for AI-assisted sperm selection?
No. It is integrated into the IVF or ICSI laboratory day.
Next steps
Related Treatments and Information Pages
Transparent use of technology
Let's Assess the Real Contribution of AI to Your Treatment
We can explain what the software measures, which clinical outcomes have been used to validate it and what it adds to conventional embryologist selection.
- Human-supervised and laboratory-validated use
- Separating algorithm performance from live-birth outcomes
- Data security, consent and version traceability
Medical sources
This content has been prepared in line with semen-analysis standards and the cautious approach in the ASRM 2026 committee opinion on the use of artificial intelligence in the IVF laboratory.