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Fast and Accurate Sperm Detection Algorithm for Micro-TESE in NOA Patients.

Mahmoud Mohamed¹, Konosuke Kachi², Kohei Motoya³

¹Laboratory for Biomaterials and Bioengineering, Institute of Science Tokyo, Tokyo 101-0062, Japan.

Bioengineering (Basel, Switzerland)

|June 26, 2025

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A new computational tool, SD-CLIP, significantly speeds up sperm detection in non-obstructive azoospermia (NOA) cases. This algorithm enhances Micro-TESE procedures, improving success rates for assisted reproductive technology (ART).

Area of Science:

Computational biology
Assisted reproductive technology
Sperm analysis

Background:

Non-obstructive azoospermia (NOA) poses challenges for assisted reproductive technology (ART) due to low sperm counts.
Manual sperm searching in Micro-TESE procedures is time-consuming and labor-intensive.

Purpose of the Study:

To develop an efficient computational tool for streamlining sperm detection in Micro-TESE.
To accelerate the identification of viable sperm in testicular tissue for ART.

Main Methods:

Introduction of SD-CLIP (Sperm Detection using Classical Image Processing), a real-time algorithm for unstained DIC images.
Utilizes edge gradients for sperm head detection and PCA for tail confirmation.

Main Results:

Keywords:

DIC microscopy Micro-TESE biomedical simulation classical image processing non-obstructive azoospermia sperm detection

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SD-CLIP demonstrated a 4x increase in processing speed and a 3.8x higher posterior probability ratio compared to MB-LBP + AKAZE.
The algorithm proved robust in low-sperm environments, validated on human and mouse testis images.

Conclusions:

SD-CLIP accurately identifies sperm morphology with high specificity, requiring minimal computational resources.
The tool supports real-time integration and has potential for automated sperm extraction, enhancing Micro-TESE and ART success rates for NOA patients.