Abstract
Defining fiber orientation at each voxel within a 3D biomedical image stack is potentially useful for a variety of applications, including cancer, wound healing and tissue regeneration. Current methods are typically computationally intensive or inaccurate. Herein, we present a 3D weighted orientation vector summation algorithm, which is a generalization of a previously reported 2D vector summation technique aimed at quantifying collagen fiber orientations simultaneously at each voxel of an image stack. As a result, voxel-wise fiber orientation information with 4° to 5° accuracy can be determined, and the computational time required to analyze a typical stack with the size of 512x512x100 voxels is less than 5 min. Thus, this technique enables the practical extraction of voxel-specific orientation data for characterizing structural anisotropy in 3D specimens. As examples, we use this approach to characterize the fiber organization in an excised mouse mammary gland and a 3D breast tissue model.
Highlights
Collagen, in the form of elongated fibrils, is the main protein of the various connective tissues in animals [1,2]
We developed a weighted orientation vector summation algorithm which is capable of detecting fiber orientation simultaneously at each pixel within a 2D image
Compared with traditional analyses that produce directional statistics based on the total orientation distribution of the image, the capability of this technique to provide voxel-wise information enables the extraction of a wider variety of potentially important diagnostic biomarkers
Summary
In the form of elongated fibrils, is the main protein of the various connective tissues in animals [1,2]. A number of techniques, such as ones based on the Fourier transform [11,12,13], Hough transform [10,14], and principal component analysis [15,16,17] are widely employed to quantify fiber orientation within two dimensional (2D) images. The applications of these 2D techniques have shown potential in providing orientation distribution information to assess collagenous tissues and understand interactions between cells and the ECM. Recent research on collagenous fibrosis has shown that 3D analysis depicts pathological changes due to fibrosis progression more precisely than 2D analysis [19,20,21]
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