Analysis of cardiac images has become fundamental for heart evaluation. It is well known that cardiac affections constitute one of the main causes of death in developed and developing countries. An early detection of cardiac diseases might substantially contribute to find the correct treatment. In this work, we propose a variational framework for left ventricle (LV) segmentation of cardiac MR and CT volumes. The method is based on a multiscale scheme provided by the Hermite transform (HT) which is used for local image feature coding. The variational approach includes several functional terms embedded into a level set - based framework in which geometrical and image features computed from coefficients of the HT are processed. Methods based on level sets are commonly configured using a set of parameters which are frequently selected experimentally. In this paper, we present an automatic mechanism for parameters selection using the contrast information obtained from the input data. The method was evaluated on several cardiac CT and MR volumes. Distance metrics were used for evaluation by comparing with manual segmentations.

Date Published: 21 December 2018
PDF: 7 pages
Proc. SPIE 10975, 14th International Symposium on Medical Information Processing and Analysis, 1097518 (21 December 2018); doi: 10.1117/12.2511591

Published in SPIE Proceedings Vol. 10975:
14th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva, Editor(s)