Quality measures for fully automatic CT histogram-based fat estimation on a corpse sample.

ABSTRACT: In a previous article a new algorithm for fully automatic 'CT histogram based Fat Estimation and quasi-Segmentation' (CFES) was validated on synthetic data, on a special CT phantom, and tested on one corpse. Usage of said data in FE-modelling for temperature-based death time estimation is the investigation's number one long-term goal. The article presents CFES's results on a human corpse sample of size R = 32, evaluating three different performance measures: the τ-value, measuring the ability to differentiate fat from muscle, the anatomical fat-muscle misclassification rate D, and the weighted distance S between the empirical and the theoretical grey-scale value histogram. CFES-performance on the sample was: D = 3.6% for weight exponent α = 1, slightly higher for α ≥ 2 and much higher for

SUBMITTER: Schenkl S 

PROVIDER: S-EPMC9684132 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature