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Groping for Quantitative Digital 3-D Image Analysis:
An Approach to Quantitative Fluorescence in situ Hybridization in
Thick Tissue Sections of Prostate Carcinoma

Karsten Rodenacker - Michaela Aubele - Peter Hutzler - P. S. Umesh Adigagif
GSF National Research Center for Environment and Health
Institute of Pathology, Dept. Biomedical Image Analysis
Ingolstädter Landstr. 1
D-85764 Neuherberg, Deutschland
Tel:+49(0)89 3187 3401 Fax:+49(0)89 3187 3349


In molecular pathology numerical chromosome aberrations have been found to be decisive for the malignancy as well as prognosis of tumors. The existence of such aberrations can be detected by interphase fluorescence in situ hybridization (FISH). The gain or loss of certain base sequences in the deoxyribonucleic acid (DNA) can be estimated by counting the number of FISH signals per cell nucleus. The quantitative evaluation of such events is a necessary condition for a prospective use in diagnostic pathology. To avoid occlusions of signals the cell nucleus has to be analyzed in three dimensions. Confocal laser scanning microscopy is the means to obtain series of optical thin sections from fluorescence stained or marked material to fulfill the conditions mentioned above.

A graphical user interface (GUI) to a software package for display, inspection, count and (semi-) automatic analysis of 3-D images for pathologists is outlined including the underlying methods of 3-D image interaction and segmentation developed. The preparative methods are shortly described. Main emphasis is given to the methodical questions of computer-aided analysis of large 3-D image data sets for pathologists. Several automated analysis steps can be performed for segmentation and succeeding quantification.

However tumor material in contrast to isolated or cultured cells is even for visual inspection a difficult material. Up to now a fully automated digital image analysis of 3-D data is not in sight. A semi-automatic segmentation method is presented.


Fluorescence in situ hybridization (FISH), Confocal laser scanning microscopy, Graphical user interface, 3-D image analysis, Segmentation

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Next: Introduction