ArticleDiagnostic pathology2013
Analyzing huge pathology images with open source software.
Article in Diagnostic pathology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
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- Single cell and spatial transcriptomics highlight the interaction of club-like cells with immunosuppressive myeloid cells in prostate cancer.Nature communications · 2024Article
- Predictive model for laser-induced tissue necrosis with immunohistochemistry validation.Biophotonics discovery · 2024Article
- High-performance Data Management for Whole Slide Image Analysis in Digital Pathology.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- ImageJ in Computational Fractal-Based Neuroscience: Pattern Extraction and Translational Research.Advances in neurobiology · 2024Article
- Reactivation of Early-Life Stress-Sensitive Neuronal Ensembles Contributes to Lifelong Stress Hypersensitivity.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Histopathological Images Analysis and Predictive Modeling Implemented in Digital Pathology-Current Affairs and Perspectives.Diagnostics (Basel, Switzerland) · 2023Review
- CTC-5: A novel digital pathology approach to characterise circulating tumour cell biodiversity.Heliyon · 2023Article
- Article
- In vivo partial reprogramming by bacteria promotes adult liver organ growth without fibrosis and tumorigenesis.Cell reports. Medicine · 2022Article
- Human hepatocyte PNPLA3-148M exacerbates rapid non-alcoholic fatty liver disease development in chimeric mice.Cell reports · 2022Article
- Role of Hepatocyte Senescence in the Activation of Hepatic Stellate Cells and Liver Fibrosis Progression.Cells · 2022Article
- Image-Guided Magnetic Thermoseed Navigation and Tumor Ablation Using a Magnetic Resonance Imaging System.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Conditions for maintenance of hepatocyte differentiation and function in 3D cultures.iScience · 2021Article
- Pharmacologic therapy for engraftment arrhythmia induced by transplantation of human cardiomyocytes.Stem cell reports · 2021Article
- Reliable computational quantification of liver fibrosis is compromised by inherent staining variation.The journal of pathology. Clinical research · 2021Article
- Colon Tissues Classification and Localization in Whole Slide Images Using Deep Learning.Diagnostics (Basel, Switzerland) · 2021Article
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6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital pathology images are increasingly used both for diagnosis and research, because slide scanners are nowadays broadly available and because the quantitative study of these images yields new insights in systems biology. However, such virtual slides build up a technical challenge since the images occupy often several gigabytes and cannot be fully opened in a computer's memory. Moreover, there is no standard format. Therefore, most common open source tools such as ImageJ fail at treating them, and the others require expensive hardware while still being prohibitively slow.
resultsWe have developed several cross-platform open source software tools to overcome these limitations. The NDPITools provide a way to transform microscopy images initially in the loosely supported NDPI format into one or several standard TIFF files, and to create mosaics (division of huge images into small ones, with or without overlap) in various TIFF and JPEG formats. They can be driven through ImageJ plugins. The LargeTIFFTools achieve similar functionality for huge TIFF images which do not fit into RAM. We test the performance of these tools on several digital slides and compare them, when applicable, to standard software. A statistical study of the cells in a tissue sample from an oligodendroglioma was performed on an average laptop computer to demonstrate the efficiency of the tools.
conclusionsOur open source software enables dealing with huge images with standard software on average computers. They are cross-platform, independent of proprietary libraries and very modular, allowing them to be used in other open source projects. They have excellent performance in terms of execution speed and RAM requirements. They open promising perspectives both to the clinician who wants to study a single slide and to the research team or data centre who do image analysis of many slides on a computer cluster. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here:http://www.diagnosticpathology.diagnomx.eu/vs/5955513929846272.
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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.