A multiresolution enhancement to generic classifiers of subcellular protein location images

We propose an algorithm for the classification of fluorescence microscopy images depicting the spatial distribution of proteins within the cell. The problem is at the forefront of the current trend in biology towards understanding the role and function of all proteins. The importance of protein subcellular location was pointed out by Murphy, whose group produced the first automated system for classification of images depicting these locations, based on diverse feature sets and combinations of classifiers. With the addition of the simplest multiresolution features, the same group obtained the high

• Type: Conference
• Year: 2006
• Where: ISBI
• Authors: Thomas E. Merryman, Keridon Williams, Gowri Srinivasa, Amina Chebira, Jelena Kovacevic
• Keywords: Diverse Feature Sets, Fluorescence Microscopy Images, ISBI 2006, Medical Imaging, Protein Subcellular Location