A metric to compare the anatomy variation between image time series
This work addresses the need for a metric to compare anatomical variations in biological processes like aging or disease, but it is incremental as it adapts an existing distance measure to a specific domain.
The paper tackles the problem of comparing anatomical changes over time between individuals or populations using image time series, proposing a generalized Fréchet distance metric to separate and quantify path and shape differences, with evaluation on simulated and neuro templates showing successful separation.
Biological processes like growth, aging, and disease progression are generally studied with follow-up scans taken at different time points, i.e., with image time series (TS) based analysis. Comparison between TS representing a biological process of two individuals/populations is of interest. A metric to quantify the difference between TS is desirable for such a comparison. The two TS represent the evolution of two different subject/population average anatomies through two paths. A method to untangle and quantify the path and inter-subject anatomy(shape) difference between the TS is presented in this paper. The proposed metric is a generalized version of Fréchet distance designed to compare curves. The proposed method is evaluated with simulated and adult and fetal neuro templates. Results show that the metric is able to separate and quantify the path and shape differences between TS.