Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2016

Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images

Résumé

Breast cancer is one of the leading causes of cancer death among women worldwide. The proposed approach comprises three steps as follows. Firstly, the image is preprocessed to remove speckle noise while preserving important features of the image. Three methods are investigated, i.e., Frost Filter, Detail Preserving Anisotropic Diffusion, and Probabilistic Patch-Based Filter. Secondly, Normalized Cut or Quick Shift is used to provide an initial segmentation map for breast lesions. Thirdly, a postprocessing step is proposed to select the correct region from a set of candidate regions. This approach is implemented on a dataset containing 20 B-mode ultrasound images, acquired from UDIAT Diagnostic Center of Sabadell, Spain. The overall system performance is determined against the ground truth images. The best system performance is achieved through the following combinations: Frost Filter with Quick Shift, Detail Preserving Anisotropic Diffusion with Normalized Cut and Probabilistic Patch-Based with Normalized Cut.
Fichier principal
Vignette du fichier
Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images.pdf (532.26 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01338131 , version 1 (28-06-2016)

Identifiants

Citer

Mohamed Elawady, Ibrahim Sadek, Abd El Rahman Shabayek, Gérard Pons, Sergi Ganau. Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound Images. Image Analysis and Recognition, 13th International Conference, ICIAR 2016, in Memory of Mohamed Kamel, Póvoa de Varzim, Portugal, July 13-15, 2016, Proceedings, 2016, 978-3-319-41500-0. ⟨10.1007/978-3-319-41501-7_24⟩. ⟨hal-01338131⟩
295 Consultations
338 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More