ArticleMedical image analysis2021
Computerized spermatogenesis staging (CSS) of mouse testis sections via quantitative histomorphological analysis.
Article in Medical image analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 45 citations in OpenAlex.
- XChondNet: Explainable Chondrogenic Tumor Diagnosis by Spatial-Context-Aware Synergistic Deep Feature Fusion.Sensors (Basel, Switzerland) · 2026Article
- Machine learning and automation methods for the segmentation, classification and quantification of testicular tissue sections.Reproduction & fertility · 2026Article
- Male germ cell-specific deletion ofZoological research · 2026Article
- Article
- Rapid detection of mouse spermatogenic defects by testicular cellular composition analysis via enhanced deep learning model.Andrology · 2025Article
- Report of the AI Pathology Task Force, Non-clinical Evaluation Expert Committee, Japan Pharmaceutical Manufacturers Association: an overview of recent publications about AI pathology.Journal of toxicologic pathology · 2025Review
- Deep-learning-based automated prediction of mouse seminiferous tubule stage by using bright-field microscopy.Scientific reports · 2025Article
- SATINN v2: automated image analysis for mouse testis histology with multi-laboratory data integration†.Biology of reproduction · 2025Article
- Differential Activity and Expression of Proteasome in Seminiferous Epithelium During Mouse Spermatogenesis.International journal of molecular sciences · 2025Article
- SIRT1 retention in elongating spermatids interferes with histone displacement by counteracting MOF-dependent H4K16 acetylation.Frontiers in cell and developmental biology · 2025Article
- Development of a procedure for isolation, identification and quality assessment of bovine spermatids and evaluation of their fertilizing abilityFrontiers in bioengineering and biotechnology · 2025Article
- Single-Cell Transcriptome Sequencing Reveals Molecular Expression Differences and Marker Genes in Testes during the Sexual Maturation of Mongolian Horses.Animals : an open access journal from MDPI · 2024Article
- Wasserstein HOG: Local Directionality Extraction via Optimal Transport.IEEE transactions on medical imaging · 2024Article
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
- Detection of spermatogonial stem/progenitor cells in prepubertal mouse testis with deep learning.Journal of assisted reproduction and genetics · 2023Article
- STAGETOOL, a Novel Automated Approach for Mouse Testis Histological Analysis.Endocrinology · 2022Article
- SATINN: an automated neural network-based classification of testicular sections allows for high-throughput histopathology of mouse mutants.Bioinformatics (Oxford, England) · 2022Article
- Cell type-specific inference of differential expression in spatial transcriptomics.Nature methods · 2022Article
- Proliferation and Apoptosis of Cat (Veterinary sciences · 2022Article
- Accurate Quantitative Histomorphometric-Mathematical Image Analysis Methodology of Rodent Testicular Tissue and Its Possible Future Research Perspectives in Andrology and Reproductive Medicine.Life (Basel, Switzerland) · 2022Article
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Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
Abstract
Spermatogenesis in mammals is a cyclic process of spermatogenic cell development in the seminiferous epithelium that can be subdivided into 12 subsequent stages. Histological staging analysis of testis sections, specifically of seminiferous tubule cross-sections, is the only effective method to evaluate the quality of the spermatogenic process and to determine developmental defects leading to infertility. Such staging analysis, however, is tedious and time-consuming, and it may take a long time to become proficient. We now have developed a Computerized Staging system of Spermatogenesis (CSS) for mouse testis sections through learning of an expert with decades of experience in mouse testis staging. The development of the CSS system comprised three major parts: 1) Developing computational image analysis models for mouse testis sections; 2) Automated classification of each seminiferous tubule cross-section into three stage groups: Early Stages (ES: stages I-V), Middle Stages (MS: stages VI-VIII), and Late Stages (LS: stages IV-XII); 3) Automated classification of MS into distinct stages VI, VII-mVIII, and late VIII based on newly developed histomorphological features. A cohort of 40 H&E stained normal mouse testis sections was built according to three modules where 28 cross-sections were leveraged for developing tubule region segmentation, spermatogenic cells types and multi-concentric-layers segmentation models. The rest of 12 testis cross-sections, approximately 2314 tubules whose stages were manually annotated by two expert testis histologists, served as the basis for developing the CSS system. The CSS system's accuracy of mean and standard deviation (MSD) in identifying ES, MS, and LS were 0.93 ± 0.03, 0.94 ± 0.11, and 0.89 ± 0.05 and 0.85 ± 0.12, 0.88 ± 0.07, and 0.96 ± 0.04 for one with 5 years of experience, respectively. The CSS system's accuracy of MSD in identifying stages VI, VII-mVIII, and late VIII are 0.74 ± 0.03, 0.85 ± 0.04, and 0.78 ± 0.06 and 0.34 ± 0.18, 0.78 ± 0.16, and 0.44 ± 0.25 for one with 5 years of experience, respectively. In terms of time it takes to collect these data, it takes on average 3 hours for a histologist and 1.87 hours for the CSS system to finish evaluating an entire testis section (computed with a PC (I7-6800k 4.0 GHzwith 32GB of RAM & 256G SSD) and a Titan 1080Ti GPU). Therefore, the CSS system is more accurate and faster compared to a human histologist in staging, and further optimization and development will not only lead to a complete staging of all 12 stages of mouse spermatogenesis but also could aid in the future diagnosis of human infertility. Moreover, the top-ranking histomorphological features identified by the CSS classifier are consistent with the primary features used by histologists in discriminating stages VI, VII-mVIII, and late VIII.
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