ArticleCommunications biology2020
Non-disruptive collagen characterization in clinical histopathology using cross-modality image synthesis.
Article in Communications biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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.
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Who cites it
18 citing papers in PubMed.
- The extracellular matrix in inflammation and cancer.Molecular biomedicine · 2026Review
- Polarimetric imaging of collagen in histopathology specimens: an investigation of congo red and picrosirius red-stained placenta and skin.Scientific reports · 2026Article
- A pathology-to-single-cell framework links SPP1Journal of translational medicine · 2026Article
- Polychromatic Polarization Microscopy Differentiates Collagen Fiber Signatures in Benign Pancreatic Tissue and Pancreatic Ductal Adenocarcinoma.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2025Article
- Geometric characteristics of stromal collagen fibres in breast cancer using differential interference contrast microscopy.Journal of microscopy · 2025Article
- Understanding the interplay between extracellular matrix topology and tumor-immune interactions: Challenges and opportunities.Oncotarget · 2024Review
- Towards next-generation diagnostic pathology: AI-empowered label-free multiphoton microscopy.Light, science & applications · 2024Review
- Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation.Medical image analysis · 2023Article
- Application of digital pathology-based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response.The Journal of pathology · 2023Review
- High-resolution confocal and light-sheet imaging of collagen 3D network architecture in very large samples.iScience · 2023Article
- Machine learning-enabled cancer diagnostics with widefield polarimetric second-harmonic generation microscopy.Scientific reports · 2022Article
- Microenvironment-mediated cancer dormancy: Insights from metastability theory.Proceedings of the National Academy of Sciences of the United States of America · 2022Review
- Artificial Intelligence and Cellular Segmentation in Tissue Microscopy Images.The American journal of pathology · 2021Review
- Machine-Learning-Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance.The American journal of pathology · 2021Review
- Real-time polarization microscopy of fibrillar collagen in histopathology.Scientific reports · 2021Article
- Mueller matrix imaging for collagen scoring in mice model of pregnancy.Scientific reports · 2021Article
- Tumor collagen framework from bright-field histology images predicts overall survival of breast carcinoma patients.Scientific reports · 2021Article
- Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning.Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The importance of fibrillar collagen topology and organization in disease progression and prognostication in different types of cancer has been characterized extensively in many research studies. These explorations have either used specialized imaging approaches, such as specific stains (e.g., picrosirius red), or advanced and costly imaging modalities (e.g., second harmonic generation imaging (SHG)) that are not currently in the clinical workflow. To facilitate the analysis of stromal biomarkers in clinical workflows, it would be ideal to have technical approaches that can characterize fibrillar collagen on standard H&E stained slides produced during routine diagnostic work. Here, we present a machine learning-based stromal collagen image synthesis algorithm that can be incorporated into existing H&E-based histopathology workflow. Specifically, this solution applies a convolutional neural network (CNN) directly onto clinically standard H&E bright field images to extract information about collagen fiber arrangement and alignment, without requiring additional specialized imaging stains, systems or equipment.
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Registered trials
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.