ArticlePloS one2017
SlideJ: An ImageJ plugin for automated processing of whole slide images.
Article in PloS one, 2017. 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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Who cites it
18 citing papers in PubMed, 37 citations in OpenAlex.
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- MetFinder: A Tool for Automated Quantitation of Metastatic Burden in Histological Sections From Preclinical Models.Pigment cell & melanoma research · 2025Article
- A suggested way forward for adoption of AI-Enabled digital pathology in low resource organizations in the developing world.Diagnostic pathology · 2023Review
- A review of open-source image analysis tools for mammalian cell culture: algorithms, features and implementations.PeerJ. Computer science · 2023Article
- Histology Image Viewer and Converter (HIVC): A High-Speed Freeware Software to View and Convert Whole Slide Histology Images.Computer methods in biomechanics and biomedical engineering. Imaging & visualization · 2023Article
- CTC-5: A novel digital pathology approach to characterise circulating tumour cell biodiversity.Heliyon · 2023Article
- Recent Advances of Deep Learning for Computational Histopathology: Principles and Applications.Cancers · 2022Review
- Artificial Intelligence-based Tumor Segmentation in Mouse Models of Lung Adenocarcinoma.Journal of pathology informatics · 2022Article
- DAB-quant: An open-source digital system for quantifying immunohistochemical staining with 3,3'-diaminobenzidine (DAB).PloS one · 2022Article
- Software tools and platforms in Digital Pathology: a review for clinicians and computer scientists.Journal of pathology informatics · 2022Review
- Whole-Slide Image Analysis of Human Pancreas Samples to Elucidate the Immunopathogenesis of Type 1 Diabetes Using the QuPath Software.Frontiers in molecular biosciences · 2021Article
- The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis.Protein science : a publication of the Protein Society · 2021Article
- Detection of HER2 from Haematoxylin-Eosin Slides Through a Cascade of Deep Learning Classifiers via Multi-Instance Learning.Journal of imaging · 2020Article
- Open software platform for automated analysis of paper-based microfluidic devices.Scientific reports · 2020Article
- Development of the automated software and device for determination of wicking in textiles using open-source tools.PloS one · 2020Article
- LibMI: An Open Source Library for Efficient Histopathological Image Processing.Journal of pathology informatics · 2020Article
- Quantitative pixel intensity- and color-based image analysis on minimally compressed files: implications for whole-slide imaging.Histochemistry and cell biology · 2019Article
- Collection of the Abstracts of the 2019Sp PMD: Translational Myology and Mobility Medicine.European journal of translational myology · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The digital slide, or Whole Slide Image, is a digital image, acquired with specific scanners, that represents a complete tissue sample or cytological specimen at microscopic level. While Whole Slide image analysis is recognized among the most interesting opportunities, the typical size of such images-up to Gpixels- can be very demanding in terms of memory requirements. Thus, while algorithms and tools for processing and analysis of single microscopic field images are available, Whole Slide images size makes the direct use of such tools prohibitive or impossible. In this work a plugin for ImageJ, named SlideJ, is proposed with the objective to seamlessly extend the application of image analysis algorithms implemented in ImageJ for single microscopic field images to a whole digital slide analysis. The plugin has been complemented by examples of macro in the ImageJ scripting language to demonstrate its use in concrete situations.
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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.