Cognition Network Technology prototype of a CAD system for mammography to assist radiologists by finding similar cases in a reference database

Schönmeyer, Ralf; Athelogou, Maria; Sittek, H.; Ellenberg, Peter; Feehan, Owen; Schmidt, Günter; Binnig, G.

doi:10.1007/s11548-010-0486-8

Cited by 10 publications

(10 citation statements)

References 9 publications

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“…The Cognition Network Technology (CNT) used in the present work represents an object-oriented image analysis approach that models human cognitive processes. Implemented in the Definiens Developer XD platform [23], it was originally developed as a tool for analysing satellite images. Recently, it was also applied to histopathology, magnetic resonance imaging and high-throughput chemical genetics [24]–[26].…”

Section: Introductionmentioning

confidence: 99%

Automated Image Analysis of the Host-Pathogen Interaction between Phagocytes and Aspergillus fumigatus

et al. 2011

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Aspergillus fumigatus is a ubiquitous airborne fungus and opportunistic human pathogen. In immunocompromised hosts, the fungus can cause life-threatening diseases like invasive pulmonary aspergillosis. Since the incidence of fungal systemic infections drastically increased over the last years, it is a major goal to investigate the pathobiology of A. fumigatus and in particular the interactions of A. fumigatus conidia with immune cells. Many of these studies include the activity of immune effector cells, in particular of macrophages, when they are confronted with conidia of A. fumigus wild-type and mutant strains. Here, we report the development of an automated analysis of confocal laser scanning microscopy images from macrophages coincubated with different A. fumigatus strains. At present, microscopy images are often analysed manually, including cell counting and determination of interrelations between cells, which is very time consuming and error-prone. Automation of this process overcomes these disadvantages and standardises the analysis, which is a prerequisite for further systems biological studies including mathematical modeling of the infection process. For this purpose, the cells in our experimental setup were differentially stained and monitored by confocal laser scanning microscopy. To perform the image analysis in an automatic fashion, we developed a ruleset that is generally applicable to phagocytosis assays and in the present case was processed by the software Definiens Developer XD. As a result of a complete image analysis we obtained features such as size, shape, number of cells and cell-cell contacts. The analysis reported here, reveals that different mutants of A. fumigatus have a major influence on the ability of macrophages to adhere and to phagocytose the respective conidia. In particular, we observe that the phagocytosis ratio and the aggregation behaviour of pksP mutant compared to wild-type conidia are both significantly increased.

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Section: Introductionmentioning

confidence: 99%

Automated Image Analysis of the Host-Pathogen Interaction between Phagocytes and Aspergillus fumigatus

et al. 2011

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“…The second method provides an alternative segmentation approach generating candidate objects from low-contrast lesions. In-depth information about the full method is reported in Schönmeyer et al [11].…”

Section: Image Databasesmentioning

confidence: 99%

“…The CADx prototype of Fraunhofer IIS provided features by the 'machine learning' approach. By contrast, the CADx and CADe prototype of Definiens' CNT introduced a new class of 'knowledge-driven' features as described by Athelogou et al [12] and Schönmeyer et al [11]. According to the definition by Horsch [13], machine learning features are typically a large number of (more or less) low-level features.…”

Section: Feature Setsmentioning

confidence: 99%

“…An iterative and cyclic development process allows features to be constructed, modified, extended, and re-used in strong interaction with an evolving development of segmentation and classification algorithms. A brief presentation of the corresponding CADe prototype can be found by Schönmeyer et al [11]. The mass segmentation approach provides 113 features for the CNTm Feature Set in total.…”

Section: The Cnt Feature Setsmentioning

confidence: 99%

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Image feature evaluation in two new mammography CAD prototypes

Hapfelmeier

Horsch

2011

Int J CARS

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“…For rule set creation, a flexible programming language called Cognition Network Language (CNL) has been constructed. Recently, CNT and CNL have been used to solve image analysis tasks in such fields as infection, cell and developmental biology [14–16] and in clinical and preclinical radiology [17, 18]. …”

Section: Introductionmentioning

confidence: 99%

Automated Segmentation and Object Classification of CT Images: Application toIn VivoMolecular Imaging of Avian Embryos

Heidrich

Schmidt

Zimmermann³

et al. 2013

International Journal of Biomedical Imaging

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Background. Although chick embryogenesis has been studied extensively, there has been growing interest in the investigation of skeletogenesis. In addition to improved poultry health and minimized economic loss, a greater understanding of skeletal abnormalities can also have implications for human medicine. True in vivo studies require noninvasive imaging techniques such as high-resolution microCT. However, the manual analysis of acquired images is both time consuming and subjective. Methods. We have developed a system for automated image segmentation that entails object-based image analysis followed by the classification of the extracted image objects. For image segmentation, a rule set was developed using Definiens image analysis software. The classification engine was implemented using the WEKA machine learning tool. Results. Our system reduces analysis time and observer bias while maintaining high accuracy. Applying the system to the quantification of long bone growth has allowed us to present the first true in ovo data for bone length growth recorded in the same chick embryos. Conclusions. The procedures developed represent an innovative approach for the automated segmentation, classification, quantification, and visualization of microCT images. MicroCT offers the possibility of performing longitudinal studies and thereby provides unique insights into the morpho- and embryogenesis of live chick embryos.

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Cognition Network Technology prototype of a CAD system for mammography to assist radiologists by finding similar cases in a reference database

Cited by 10 publications

References 9 publications

Automated Image Analysis of the Host-Pathogen Interaction between Phagocytes and Aspergillus fumigatus

Automated Image Analysis of the Host-Pathogen Interaction between Phagocytes and Aspergillus fumigatus

Image feature evaluation in two new mammography CAD prototypes

Automated Segmentation and Object Classification of CT Images: Application toIn VivoMolecular Imaging of Avian Embryos

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