Abstract
Automated processing and quantification of biological images have been rapidly increasing the attention of
researchers in image processing and pattern recognition because the roles of computerized image and pattern
analyses are critical for new biological findings and drug discovery based on modern high-throughput and highcontent
image screening. This paper presents a study of the automated detection of regions of mitochondria,
which are a subcellular structure of eukaryotic cells, in microscopy images. The automated identification of
mitochondria in intracellular space that is captured by the state-of-the-art combination of focused ion beam and
scanning electron microscope imaging reported here is the first of its type. Existing methods and a proposed
algorithm for texture analysis were tested with the real intracellular images. The high correction rate of detecting
the locations of the mitochondria in a complex environment suggests the effectiveness of the proposed study.