Evidence map›Paper›PMID 41596033›Full record

ArticleBioengineering (Basel, Switzerland)2026

AI-Based Augmented Reality Microscope for Real-Time Sperm Detection and Tracking in Micro-TESE.

Mahmoud Mohamed, Ezaki Yuriko, Yuta Kawagoe, Kazuhiro Kawamura, Masashi Ikeuchi

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mahmoud MohamedLaboratory for Biomaterials and Bioengineering, Institute of Science Tokyo, Tokyo 152-8550, Japan.ORCID 0000-0002-8390-0711
Ezaki YurikoGraduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-8654, Japan.
Yuta KawagoeLaboratory for Biomaterials and Bioengineering, Institute of Science Tokyo, Tokyo 152-8550, Japan.
Kazuhiro KawamuraDepartments of Obstetrics and Gynecology, Juntendo University Faculty of Medicine, Tokyo 113-8421, Japan.ORCID 0000-0001-5572-9171
Masashi IkeuchiLaboratory for Biomaterials and Bioengineering, Institute of Science Tokyo, Tokyo 152-8550, Japan.ORCID 0009-0000-6778-4522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-obstructive azoospermia (NOA) is a severe male infertility condition characterized by extremely low or absent sperm production. In microdissection testicular sperm extraction (Micro-TESE) procedures for NOA, embryologists must manually search through testicular tissue under a microscope for rare sperm, a process that can take 1.8-7.5 h and impose significant fatigue and burden. This paper presents an augmented reality (AR) microscope system with AI-based image analysis to accelerate sperm retrieval in Micro-TESE. The proposed system integrates a deep learning model (YOLOv5) for real-time sperm detection in microscope images, a multi-object tracker (DeepSORT) for continuous sperm tracking, and a velocity calculation module for sperm motility analysis. Detected sperm positions and motility metrics are overlaid in the microscope's eyepiece view via a microdisplay, providing immediate visual guidance to the embryologist. In experiments on seminiferous tubule sample images, the YOLOv5 model achieved a precision of 0.81 and recall of 0.52, outperforming previous classical methods in accuracy and speed. The AR interface allowed an operator to find sperm faster, roughly doubling the sperm detection rate (66.9% vs. 30.8%). These results demonstrate that the AR microscope system can significantly aid embryologists by highlighting sperm in real time and potentially shorten Micro-TESE procedure times. This application of AR and AI in sperm retrieval shows promise for improving outcomes in assisted reproductive technology.

Indexed as

augmented reality microscopedeep learningMicro-TESEnon-obstructive azoospermiaobject trackingsperm detectionsperm motility analysis

Identifiers

PMID41596033
PMCPMC12837562

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.