Special issue on microscopic image processing

Microscopic images play an essential role in detection and diagnosis of numerous diseases. For example, analysis of histology images of the human tissue biopsies remains the most reliable way of diagnosis and grading cancer. On the other hand, there is significant interand intra-rater variability in the grading and diagnosis of cancer from histology slides by clinicians. Computational histopathology can assist the pathologists in making the grading and diagnosis reproducible, by providing useful quantitative measures from histology images of a patient suspected or diagnosed of having cancer [1]. Similarly, in cellular biology, live cell fluorescence imagingmade possible by the rapid advances of fluorescent microscopy opens new avenues for microscopic image processing. It is possible to give many similar examples. In this special issue, we bring together six recent research articles on microscopic image processing and analysis. The subject topics of papers cover a diverse set of topics related to microscopic images processing such as creating efficient representations, segmentation of diagnostically significant structures, and automated classification. Even if the targeted applications are diverse, the main goal of all the algorithms was similar; they describe automated analysis methods for