Semi-automatic segmentation of whole-body images in longitudinal studies.
Biomed Phys Eng Express
; 7(1)2020 12 08.
Article
en En
| MEDLINE
| ID: mdl-34983886
ABSTRACT
We propose a semi-automatic segmentation pipeline designed for longitudinal studies considering structures with large anatomical variability, where expert interactions are required for relevant segmentations. Our pipeline builds on the regularized Fast Marching (rFM) segmentation approach by Risseret al(2018). It consists in transporting baseline multi-label FM seeds on follow-up images, selecting the relevant ones and finally performing the rFM approach. It showed increased, robust and faster results compared to clinical manual segmentation. Our method was evaluated on 3D synthetic images and patients' whole-body MRI. It allowed a robust and flexible handling of organs longitudinal deformations while considerably reducing manual interventions.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Imagen Corporal
/
Imagen por Resonancia Magnética
Tipo de estudio:
Guideline
/
Observational_studies
Límite:
Humans
Idioma:
En
Revista:
Biomed Phys Eng Express
Año:
2020
Tipo del documento:
Article
País de afiliación:
Francia