ArticleDiagnostic pathology2013
CognitionMaster: an object-based image analysis framework.
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 15 papers.
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Who cites it
15 citing papers in PubMed.
- A Non-interventional Clinical Trial Assessing Immune Responses After Radiofrequency Ablation of Liver Metastases From Colorectal Cancer.Frontiers in immunology · 2019Trial
- A comparison of pixel intensity-based and object-based image analysis software algorithms for assessing immunohistochemical staining of sections from paraffin-embedded human tumor samples.Histochemistry and cell biology · 2025Article
- Slow integrin-dependent migration organizes networks of tissue-resident mast cells.Nature immunology · 2023Article
- Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2022Article
- An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma.Nature communications · 2019Article
- Tissue clonality of dendritic cell subsets and emergency DCpoiesis revealed by multicolor fate mapping of DC progenitors.Science immunology · 2019Article
- An international multicenter study to evaluate reproducibility of automated scoring for assessment of Ki67 in breast cancer.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2019Article
- The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer.PloS one · 2018Article
- DNA copy number changes define spatial patterns of heterogeneity in colorectal cancer.Nature communications · 2017Article
- Article
- [CD15 focus score for diagnostics of periprosthetic joint infections : Neutrophilic granulocytes quantification mode and the development of morphometric software (CD15 quantifier)].Zeitschrift fur Rheumatologie · 2015Article
- Conference report from the 2015 OECI Oncology Days, Portugal, 22-24 June-tumour heterogeneity and next generation sequencing: morphology and technology.Ecancermedicalscience · 2015Article
- Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks.PloS one · 2014Article
- Multicolor fate mapping of Langerhans cell homeostasis.The Journal of experimental medicine · 2013Article
- Analyzing huge pathology images with open source software.Diagnostic pathology · 2013Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAutomated image analysis methods are becoming more and more important to extract and quantify image features in microscopy-based biomedical studies and several commercial or open-source tools are available. However, most of the approaches rely on pixel-wise operations, a concept that has limitations when high-level object features and relationships between objects are studied and if user-interactivity on the object-level is desired.
resultsIn this paper we present an open-source software that facilitates the analysis of content features and object relationships by using objects as basic processing unit instead of individual pixels. Our approach enables also users without programming knowledge to compose "analysis pipelines" that exploit the object-level approach. We demonstrate the design and use of example pipelines for the immunohistochemistry-based cell proliferation quantification in breast cancer and two-photon fluorescence microscopy data about bone-osteoclast interaction, which underline the advantages of the object-based concept.
conclusionsWe introduce an open source software system that offers object-based image analysis. The object-based concept allows for a straight-forward development of object-related interactive or fully automated image analysis solutions. The presented software may therefore serve as a basis for various applications in the field of digital image analysis.
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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.