Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue.

ABSTRACT: Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic 'divide and conquer' methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick ( approximately 100 microm) slices of rat brain tissue were labeled using three to five fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features wer

SUBMITTER: Bjornsson CS 

PROVIDER: S-EPMC2700351 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature