Abstract
Biomedicine has seen tremendous advances in the field of image acquisition. The generation of digital images of high information content has become so straightforward and efficient that the volume of images accumulating in biomedical disciplines is posing significant challenges. Until now, conventional image analysis solutions are generally pixel-based and limited in the amount of information that they extract. However, a software system enabling the complex analysis of biomedical images should not impose restrictions on detection, classification and quantification of structures, but rather allow unlimited freedom to answer exhaustively all conceivable questions about the interactions and relationships between structures. Crucial to this is the precise and robust segmentation of relevant structures in digital micrographs. This challenge involves bringing structure, morphology and context into play. Based on the Definiens Cognition Network Technology®, solutions have been deployed for use in biomedicine. The technology is object-oriented, multi-scale, context-driven and knowledge-based. Images are interpreted on the properties of networked image objects, which results in numerous advantages. This approach enables users to bring in detailed expert knowledge and enables complex analyses to be performed with unprecedented accuracy, even on poor quality data or for structures exhibiting heterogeneous properties or variable phenotypes. Extracted structures are the basis for detailed morphometric, structural and relational measurements which can be exported for each individual structure. These data can be used for decision support or correlated against experimental or molecular data, thus bridging classical biomedicine with molecular biology. An overview of the technology is provided with examples from different biomedical applications.
Combinatorial Chemistry & High Throughput Screening
Title: Automated Analysis and Detailed Quantification of Biomedical Images Using Definiens Cognition Network Technology®
Volume: 12 Issue: 9
Author(s): Martin Baatz, Johannes Zimmermann and Colin G. Blackmore
Affiliation:
Abstract: Biomedicine has seen tremendous advances in the field of image acquisition. The generation of digital images of high information content has become so straightforward and efficient that the volume of images accumulating in biomedical disciplines is posing significant challenges. Until now, conventional image analysis solutions are generally pixel-based and limited in the amount of information that they extract. However, a software system enabling the complex analysis of biomedical images should not impose restrictions on detection, classification and quantification of structures, but rather allow unlimited freedom to answer exhaustively all conceivable questions about the interactions and relationships between structures. Crucial to this is the precise and robust segmentation of relevant structures in digital micrographs. This challenge involves bringing structure, morphology and context into play. Based on the Definiens Cognition Network Technology®, solutions have been deployed for use in biomedicine. The technology is object-oriented, multi-scale, context-driven and knowledge-based. Images are interpreted on the properties of networked image objects, which results in numerous advantages. This approach enables users to bring in detailed expert knowledge and enables complex analyses to be performed with unprecedented accuracy, even on poor quality data or for structures exhibiting heterogeneous properties or variable phenotypes. Extracted structures are the basis for detailed morphometric, structural and relational measurements which can be exported for each individual structure. These data can be used for decision support or correlated against experimental or molecular data, thus bridging classical biomedicine with molecular biology. An overview of the technology is provided with examples from different biomedical applications.
Export Options
About this article
Cite this article as:
Baatz Martin, Zimmermann Johannes and Blackmore G. Colin, Automated Analysis and Detailed Quantification of Biomedical Images Using Definiens Cognition Network Technology®, Combinatorial Chemistry & High Throughput Screening 2009; 12 (9) . https://dx.doi.org/10.2174/138620709789383196
DOI https://dx.doi.org/10.2174/138620709789383196 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
Call for Papers in Thematic Issues
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the ...read more
Eco-friendly Agents for Biological Control of Pathogenic Diseases
The discovery of an alternative biological approach to disease management includes work on medicinal products derived from natural sources as a starting point for the development of eco-friendly agents for these diseases and the injuries they cause, as well as reducing human contact with hazardous chemicals and their residues. We ...read more
Emerging trends in diseases mechanisms, noble drug targets and therapeutic strategies: focus on immunological and inflammatory disorders
Recently infectious and inflammatory diseases have been a key concern worldwide due to tremendous morbidity and mortality world Wide. Recent, nCOVID-9 pandemic is a good example for the emerging infectious disease outbreak. The world is facing many emerging and re-emerging diseases out breaks at present however, there is huge lack ...read more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Scope of the Thematic Issue: Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute force experimentation, which can be time-consuming and resource-intensive. Spectral Graph Theory, a branch of mathematics dealing with the properties of graphs in relation to the ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Molecular Pharmacology and Pharmacogenomics of Artemisinin and its Derivatives in Cancer Cells
Current Drug Targets Bone Metastasis: Molecular Mechanisms Implicated in Tumour Cell Dormancy in Breast and Prostate Cancer
Current Cancer Drug Targets Virus, Oncolytic Virus and Human Prostate Cancer
Current Cancer Drug Targets Ferroptosis Inducers for Prostate Cancer Therapy
Current Medicinal Chemistry Adenoviral Vector-Mediated Gene Transfer for Human Gene Therapy
Current Gene Therapy Regulators of Chemokine Receptor Activity as Promising Anticancer Therapeutics
Current Cancer Drug Targets Diagnostic Performance of Magnetic Resonance Cholangiopancreatography (MRCP) for Biliopancreatic Cancer
Current Medical Imaging A Quantitative Proteomics Approach in the Study of MicroRNA 181a in HepG2 Cells
Current Proteomics DYRK1A Kinase Inhibitors with Emphasis on Cancer
Mini-Reviews in Medicinal Chemistry The Antitumor Effects of Britanin on Hepatocellular Carcinoma Cells and its Real-Time Evaluation by In Vivo Bioluminescence Imaging
Anti-Cancer Agents in Medicinal Chemistry Cell Dormancy and Tumor Refractory
Anti-Cancer Agents in Medicinal Chemistry Discovery of Novel Regulatory Peptides by Reverse Pharmacology: Spotlight on Chemerin and the RF-amide Peptides Metastin and QRFP
Current Protein & Peptide Science Copper Compounds in Anticancer Strategies
Current Medicinal Chemistry Chlorella vulgaris: A Multifunctional Dietary Supplement with Diverse Medicinal Properties
Current Pharmaceutical Design Development of <sup>186/188</sup>Re-Chitosan as an Effective Therapeutic Agent for Rheumatoid Arthritis
Current Radiopharmaceuticals Editorial [Hot Topic: Mechanisms of Drug Sensitivity and Resistance in Cancer (Guest Editor: Lorraine ODriscoll)]
Current Cancer Drug Targets Anti-VEGF Mediated Immunomodulatory Role of Phytochemicals: Scientific Exposition for Plausible HCC Treatment
Current Drug Targets Bioinorganic Chemistry: The Study of the Fate of Platinum-Based Antitumour Drugs
Current Chemical Biology Therapeutic microRNA Delivery Strategies with Special Emphasis on Cancer Therapy and Tumorigenesis: Current Trends and Future Challenges
Current Drug Metabolism RNA Interference as Therapeutics for Hepatocellular Carcinoma
Recent Patents on Anti-Cancer Drug Discovery