Semi-automated color segmentation from a biological cross-sectional image series: follicle segmentation from the equine ovary

This paper proposes a semi-automatic segmentation method for the 3D-ISM system, which enables the capture of a high-resolution full-color cross sectional image series of a biological sample. Our approach is based on region-based segmentation and an adaptive classification technique by using the Otsu method, so it can be applied to an object like biological tissue, which has different colors by location. As a result, we have achieved to develop the method to decrease the degree of manual operation required. This paper also shows experimental results of applying our method to visualize the internal structure of the equine ovary. We have confirmed the spatial arrangement inside the ovary, which had not been revealed so far.