Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Sperm YOLOv8E-TrackEVD: A Novel Approach for Sperm Detection and Tracking

28 May 2024

Abstract excerpt

Male infertility is a global health issue, with 40-50% attributed to sperm abnormalities. The subjectivity and irreproducibility of existing detection methods pose challenges to sperm assessment, making the design of automated semen analysis algorithms crucial for enhancing the reliability of sperm evaluations. This paper proposes a comprehensive sperm tracking algorithm (Sperm YOLOv8E-TrackEVD) that combines an...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Reproductive Biology and Fertility
Share to Reproductive Health and Technologies
Share to Sperm and Testicular Function

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 38894284
DOI: 10.3390/s24113493

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Sperm YOLOv8E-TrackEVD: A Novel Approach for Sperm Detection and TrackingPMID 38894284Read ↗

Automated Non-Invasive Analysis of Motile Sperms Using Sperm Feature-Correlated NetworkSemantic proximity Read ↗

Multidimensional morphological analysis of live sperm based on multiple-target trackingSemantic proximity Read ↗

Deep Learning-Based Morphological Classification of Human Sperm HeadsSemantic proximity Read ↗

Automatic identification of human spermatozoa with zona pellucida-binding capability using deep learningSemantic proximity Read ↗

Category-Aware Two-Stage Divide-and-Ensemble Framework for Sperm Morphology ClassificationSemantic proximity Read ↗

Deep Learning-enabled Sperm Morphology Analysis of Bovine Sperm for label-free Imaging Flow CytometrySemantic proximity Read ↗

Deep learning-based selection of human sperm with high DNA integritySemantic proximity Read ↗

Simultaneous Morphology, Motility, and Fragmentation Analysis of Live Individual Sperm Cells for Male Fertility EvaluationSemantic proximity Read ↗

Sperm‐cell DNA fragmentation prediction using label‐free quantitative phase imaging and deep learningSemantic proximity Read ↗

Continuous Motility Fingerprints from Gaussian Mixture Models Reveal Hidden Sperm HeterogeneitySemantic proximity Read ↗

Deep Learning-Based Robust Automated System for Predicting Human Sperm DNA Fragmentation IndexSemantic proximity Read ↗

Exploration of the Clinical Application of Multimodal Artificial Intelligence in Sperm Screening: Identifying Opportunities and Addressing ChallengesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.