ArticleScientific reports2017
PathoSpotter-K: A computational tool for the automatic identification of glomerular lesions in histological images of kidneys.
Article in Scientific reports, 2017. 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.
- Biological feature-based machine learning in histopathological images: a systematic review.Journal of pathology informatics · 2026Review
- Unsupervised stain augmentation enhanced glomerular instance segmentation on pathology images.International journal of computer assisted radiology and surgery · 2025Article
- Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.Bioinformatics (Oxford, England) · 2024Article
- Enhancing Podocyte Degenerative Changes Identification With Pathologist Collaboration: Implications for Improved Diagnosis in Kidney Diseases.IEEE journal of translational engineering in health and medicine · 2024Article
- A Spatially Guided Machine-Learning Method to Classify and Quantify Glomerular Patterns of Injury in Histology Images.Journal of imaging · 2023Article
- Automatic Identification of Glomerular in Whole-Slide Images Using a Modified UNet Model.Diagnostics (Basel, Switzerland) · 2023Article
- Artificial intelligence in renal pathology: Current status and future.Biomolecules & biomedicine · 2023Review
- Accurate Kidney Pathological Image Classification Method Based on Deep Learning and Multi-Modal Fusion Method with Application to Membranous Nephropathy.Life (Basel, Switzerland) · 2023Article
- Glo-In-One: holistic glomerular detection, segmentation, and lesion characterization with large-scale web image mining.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Artificial Intelligence-Assisted Renal Pathology: Advances and Prospects.Journal of clinical medicine · 2022Review
- Glomerular disease classification and lesion identification by machine learning.Biomedical journal · 2022Article
- Explainable Biomarkers for Automated Glomerular and Patient-Level Disease Classification.Kidney360 · 2022Article
- Evaluation of Kidney Histological Images Using Unsupervised Deep Learning.Kidney international reports · 2021Article
- Map3D: Registration-Based Multi-Object Tracking on 3D Serial Whole Slide Images.IEEE transactions on medical imaging · 2021Article
- AI applications in renal pathology.Kidney international · 2021Review
- Glomerular Classification Using Convolutional Neural Networks Based on Defined Annotation Criteria and Concordance Evaluation Among Clinicians.Kidney international reports · 2021Article
- Instance segmentation for whole slide imaging: end-to-end or detect-then-segment.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning.The Journal of pathology · 2020Article
- Hierarchical Clustering Analysis for Predicting 1-Year Mortality After Starting Hemodialysis.Kidney international reports · 2020Article
- Machine learning, the kidney, and genotype-phenotype analysis.Kidney international · 2020Review
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4 authors.
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Abstract
PathoSpotter is a computational system designed to assist pathologists in teaching about and researching kidney diseases. PathoSpotter-K is the version that was developed to detect nephrological lesions in digital images of kidneys. Here, we present the results obtained using the first version of PathoSpotter-K, which uses classical image processing and pattern recognition methods to detect proliferative glomerular lesions with an accuracy of 88.3 ± 3.6%. Such performance is only achieved by similar systems if they use images of cell in contexts that are much less complex than the glomerular structure. The results indicate that the approach can be applied to the development of systems designed to train pathology students and to assist pathologists in determining large-scale clinicopathological correlations in morphological research.
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