Fluorescent in-situ hybridization (FISH) and immunohistochemistry (IHC) constitute a pair of complimentary techniques for detecting gene amplification and overexpression, respectively. The advantages of IHC include relatively cheap materials and high sample durability, while FISH is the more accurate and reproducible method. Evaluation of FISH and IHC images is still largely performed manually, with automated or semiautomated techniques increasing in popularity. Here, we provide a comprehensive review of a number of (semi-) automated FISH and IHC image processing systems, focusing on the algorithmic aspects of each technique. Our review verifies the increasingly important role of such methods in FISH and IHC; however, manual intervention is still necessary in order to resolve particularly challenging or ambiguous cases. In addition, large-scale validation is required in order for these systems to enter standard clinical practice. q 2007 International Society for Analytical Cytology Key terms: fluorescent in situ hybridization (FISH); immunohistochemistry (IHC); image analysis techniques; nuclei segmentation; spot detection; antibody staining A variety of methods are available for the detection of gene status in tissue samples, with fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) being two of the most prominent ones for detecting gene amplification and overexpression, respectively. Both techniques permit the study of small amounts of formalinfixed, paraffin-embedded tissue and the interpretation of the findings on a cell-by-cell basis. FISH allows selective staining of various DNA sequences with fluorescent markers, and thereby the detection, analysis, and quantification of specific numerical and structural abnormalities within nuclei. This procedure has proven to be as accurate as Southern blot analysis, while allowing the measurement of the fraction of amplified cells and the intercellular heterogeneity within a given cell population (1,2). On the other hand, IHC uses specific antibodies to stain proteins in situ, which allows the identification of many cell types that could be visualized by classical microscopy.FISH is a direct in situ technique that is relatively rapid and sensitive. No cell culture is needed to apply this method and results are easier to interpret than karyotype. The FISH technique has the advantages of a more objective scoring system and the presence of a built-in internal control consisting of the two Her-2/neu gene signals present in all nonneoplastic cells of the specimen. Disadvantages of FISH testing include the high cost of each test, long time needed for slide scoring, requirement for a fluorescence microscope, inability to preserve the acquired sample for storage and review, and, occasional difficulty in identifying the invasive tumor cells (3). On the other hand, advantages of IHC testing include its wide availability, relatively low cost, easy and long preservation of stained slides, and use of an ordinary light microscope. Disadvantages of IHC include the...

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The proliferation of social platforms and the enhanced connectivity have led people of different age groups, ethnicity, social or economic status to reveal a great deal about themselves online. Data collected from online social networks (OSN) provides social, economic, and cultural information which can be utilized by governments, policy makers, authorities and even commercial industries to better understand market trends and behavioral patterns, that can influence the individual dynamics through open data sources. OSN constitute a breeding ground for the spread of several risks and threats to privacy and security that affect participation and quality of life in smart cities. Although the aspects of privacy and security, and individuals' behavior in social networking are important for the successful development of smart cities, they have not been adequately discussed. To this end, this study aims to address this issue by revealing the risks, threats and individuals' behavior on OSN as an attempt to enhance privacy and security, and boost community's engagement in smart cities. Furthermore, a novel model which outlines the relationships between privacy and security threats, along with some effective countermeasures for the protection of OSN users in smart cities are proposed.

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