Jelly filling segmentation of fluorescence microscopy images containing incomplete labeling

Biological images acquired using fluorescence microscopy typically suffer from poor edge details, non-uniform brightness, decreasing image contrast with tissue depth and irregular/unknown structure. Hence they are consequently challenging to segment. In this paper, we present a segmentation method we call "Jelly filling" for analyzing biological volumes that also contain incomplete labeling. Our method uses adaptive thresholding, component analysis, and three-dimensional structural consistency to iteratively refine segments that represent physical quantities. Preliminary results obtained using fluorescence microscopy images of rat kidneys demonstrate the efficacy of the proposed method.