Nonlinear tube-fitting for the analysis of anatomical and functional structures

TL;DR

This paper introduces a novel nonlinear tube-fitting algorithm for estimating the surfaces of anatomical tube-shaped structures, validated through simulations and applied to colon and brain imaging data.

Contribution

The paper presents a new tube-fitting method for 3D support estimation, with validation and application to medical imaging data for anatomical analysis.

Findings

Effective in estimating anatomical tube structures

Validated through simulation and real data applications

Applicable to colon SPECT and brain DTI images

Abstract

We are concerned with the estimation of the exterior surface and interior summaries of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goals, one dealing with the distribution of HIV microbicide in the colon and the other with measuring degradation in white-matter tracts in the brain. Our problem is posed as the estimation of the support of a distribution in three dimensions from a sample from that distribution, possibly measured with error. We propose a novel tube-fitting algorithm to construct such estimators. Further, we conduct a simulation study to aid in the choice of a key parameter of the algorithm, and we test our algorithm with validation study tailored to the motivating data sets. Finally, we apply the tube-fitting algorithm to a colon image produced by single photon emission computed tomography (SPECT) and to a white-matter tract image produced using diffusion tensor imaging (DTI).