Computational technologies are used to accelerate or fully automate the processing, quantification and analysis of large amounts of high-information-content biomedical imagery. Modern image analysis systems augment an observer's ability to make measurements from a large or complex set of images, by improving accuracy, objectivity or speed. A fully developed analysis system may completely replace the observer. Although these systems are not unique to biomedical imagery, biomedical imaging is becoming more important for both diagnostics and research. Some examples are high-throughput and high-fidelity quantification & sub-cellular localization, morphometrics, clinical image analysis & visualization, infrared measurements for metabolic activity determination. Image analysis related techniques (like wavelet) have also been found useful in bioinformatics problems, such as sequence analysis. The potential of mining the information in bioimages to answer biological questions is enormous and it cries for advanced techniques of bioimage data mining & informatics