Segmentation algorithms for ear image data towards biomechanical studies

• Tipo: Artigo em Revista Científica Internacional
• Data: 2014

Autores

Ana Ferreira (Autor) Outra; Fernanda Gentil (Autor) Outra; João Manuel R. S. Tavares (Autor) FEUP

Revista

Título: Computer Methods in Biomechanics and Biomedical Engineering

Vol. 17 Nº 2

Páginas: 888-904

ISSN: 1025-5842

Editora: Taylor & Francis

Indexação

ISI Web of Knowledge - 20 Citações

ISI Web of Science

Scopus - 36 Citações

COMPENDEX

INSPEC

Classificação Científica

FOS: Ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas

Outras Informações

ID Authenticus: P-009-7PD

DOI: 10.1080/10255842.2012.723700

Abstract (EN): In recent years, the segmentation, i.e. the identification, of ear structures in video-otoscopy, computerised tomography (CT) and magnetic resonance (MR) image data, has gained significant importance in the medical imaging area, particularly those in CT and MR imaging. Segmentation is the fundamental step of any automated technique for supporting the medical diagnosis and, in particular, in biomechanics studies, for building realistic geometric models of ear structures. In this paper, a review of the algorithms used in ear segmentation is presented. The review includes an introduction to the usually biomechanical modelling approaches and also to the common imaging modalities. Afterwards, several segmentation algorithms for ear image data are described, and their specificities and difficulties as well as their advantages and disadvantages are identified and analysed using experimental examples. Finally, the conclusions are presented as well as a discussion about possible trends for future research concerning the ear segmentation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 17