Systems for detecting and analyzing target patterns in digital imagery have a wide variety of uses. One such use is analyzing anatomical regions in radiological images. For example, systems for analyzing computed tomography (CT) images are used for the computer-aided detection of cancerous regions in human breasts and lungs. Another use for such image analysis systems is to detect and analyze target patterns in biomedical images obtained from microscopes, such as confocal microscopes. For example, pathologists use confocal microscopes to analyze cells and their components, such as organelles, membranes, nuclei, genes, chromosomes and macromolecules such as RNA, DNA, proteins and peptides. Such image analysis is used not only in diagnosis and prognosis relating to medical patients, but also in basic research, drug discovery and clinical trials.
Confocal microscopy offers several advantages over conventional optical microscopy by providing a wider depth of field, eliminating out-of-focus glare, and allowing the collection of serial optical sections from thick specimens. The laser scanning confocal microscope (LSCM) is currently the most widely used confocal microscope for biomedical research applications. In the biomedical sciences, a major application of confocal microscopy involves imaging cells and cell components that have been labeled with biomarkers, such as fluorescent probes. Confocal microscopy in combination with in situ hybridization and fluorescence techniques can be used to study DNA and RNA sequences in chromosomes and to analyze cell components, such as chromosomes and genes. One such technique for analyzing cell components is Fluorescence in situ Hybridization (FISH). For additional information on the FISH technique, see U.S. patent application Ser. No. 11/050,035, published on Dec. 1, 2005 as Publication No. 2005/0265588 A1, by Gholap et al. (the entirety of which is incorporated herein by reference).
In one specific application, FISH is used to analyze the Her-2/neural gene in breast biopsies in order to provide a diagnosis and prognosis for breast cancer. Using confocal microscopy in combination with FISH, a pathologist calculates the degree of gene amplification as the basis for the diagnosis. In one accepted diagnostic procedure, the pathologist analyzes a minimum of one hundred nuclei in order to calculate the degree of amplification. In this conventional procedure, the pathologist manually counts the marked chromosomes and genes (called “fluorescence signals”) in each of the one hundred nuclei and then calculates the ratios of the genes to the chromosomes. A disadvantage of this conventional procedure is that even an experienced pathologist may miss some of the fluorescence signals due to fatigue and loss of concentration. Most of the biopsies contain normal counts of marked genes and chromosomes, and the pathologist may lose concentration with the tedium of counting genes and chromosomes in hundreds of nuclei in multiple biopsies. Moreover, determining whether a fluorescence signal represents a single gene or multiple overlapping genes based on the brightness and size of the fluorescence signal is often a subjective determination. Individual pathologists may have different counting styles.
Thus, an automated system for counting fluorescence signals obtained from the FISH technique is desired. Existing automated counting systems count fluorescence signals based on two-dimensional images. See, e.g., Gholap et al., Pub. No. 2005/0265588 A1, cited above. Even in existing systems that obtain three-dimensional information using confocal microscopy, however, the systems analyze two-dimensional images obtained by condensing the three-dimensional information, thereby losing much of the three-dimensional information. It is difficult to distinguish individual nuclei and other cell components in two-dimensional composite images obtained by condensing three-dimensional information. Fluorescence signals that touch or overlap other signals cannot be accurately counted. In addition, information concerning the distance between signals and the size of individual signals is lost. Thus, a system is sought for automatically counting fluorescence signals that are present in three dimensions in slides obtained using the FISH technique.
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