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
-
Mouse Induced Glioma-Initiating Cell Models and Therapeutic Targets
Anti-Cancer Agents in Medicinal Chemistry vHTS, 3-D Pharmacophore, QSAR and Molecular Docking Studies for the Identification of Phyto-derived ATP-Competitive Inhibitors of the BCR-ABL Kinase Domain
Current Drug Discovery Technologies Synthesis of a Tyr-Tyr Dipeptide Library and Evaluation Against Tumor Cells
Medicinal Chemistry The Expanding Role of Tumor Necrosis Factor-α Inhibitors in the Management of Rheumatic Diseases
Medicinal Chemistry Reviews - Online (Discontinued) Evaluation of Non-Coding RNAs as Potential Targets in Head and Neck Squamous Cell Carcinoma Cancer Stem Cells
Current Drug Targets Mitochondrial Dysfunction in Gliomas: Pharmacotherapeutic Potential of Natural Compounds
Current Neuropharmacology Stereoselective Metabolic and Pharmacokinetic Analysis of the Chiral Active Components from Herbal Medicines
Current Pharmaceutical Analysis Does Cyclic Dependent Kinase 5 Play a Significant Role in Determination of Stroke Outcome? Possible Therapeutic Implications
Central Nervous System Agents in Medicinal Chemistry Synthesis and Properties of 14-epi-1α,25-Dihydroxy-19-Nortachysterol and its 2-Substituted Derivatives
Current Topics in Medicinal Chemistry Therapeutic Antibodies
Current Molecular Medicine Antibody Gene Therapy: Getting Closer to Clinical Application?
Current Gene Therapy Synthesis, EGFR Inhibition and Anti-cancer Activity of New 3,6-dimethyl-1-phenyl-4-(substituted-methoxy)pyrazolo[3,4-d] pyrimidine Derivatives
Anti-Cancer Agents in Medicinal Chemistry MicroRNA as Regulators of Cancer Stem Cells and Chemoresistance in Colorectal Cancer
Current Cancer Drug Targets Tea and Health: Studies in Humans
Current Pharmaceutical Design Prevention and Treatment of Bone Metastases
Current Pharmaceutical Design A Machine Learning-based Self-risk Assessment Technique for Cervical Cancer
Current Bioinformatics The Effect of Recombinant Human Interferon Alpha Nasal Drops to Prevent COVID-19 Pneumonia for Medical Staff in an Epidemic Area
Current Topics in Medicinal Chemistry An Approach to Treatment of Liver Cancer by Novel Glycyrrhizin Derivative
Anti-Cancer Agents in Medicinal Chemistry Recent Developments to Improve the Efficacy of Cytotoxic Nucleoside Analogues
Recent Patents on Anti-Cancer Drug Discovery Non Steroidal Estrogen Antagonists: Current Status and Future Perspectives
Current Medicinal Chemistry - Immunology, Endocrine & Metabolic Agents