Classifying Ductal Tree Structures Using Topological Descriptors of Branching - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2011

Classifying Ductal Tree Structures Using Topological Descriptors of Branching

Angeliki Skoura
  • Fonction : Auteur
  • PersonId : 1014231
Vasileios Megalooikonomou
  • Fonction : Auteur
  • PersonId : 992351
Predrag R. Bakic
  • Fonction : Auteur
  • PersonId : 1014232
Andrew Maidment
  • Fonction : Auteur
  • PersonId : 1014233

Résumé

We propose a methodological framework for the classification of the tree-like structures of the ductal network of human breast regarding radiological findings related to breast cancer. Initially we perform the necessary preprocessing steps such as image segmentation in order to isolate the ductal tree structure from the background of x-ray galactograms. Afterwards, we employ tree characterization approaches to obtain a symbolic representation of the distribution of trees’ branching points. Our methodology is based on Sholl analysis, a technique which uses concentric circles that radiate from the center of the region of interest. Finally, we apply the k-nearest neighbor classification scheme to characterize the tree-like ductal structures in galactograms in order to distinguish among different radiological findings. The experimental results are quite promising as the classification accuracy reaches up to 82% indicating that our methods may assist radiologists to identify image biomarkers in galactograms.
Fichier principal
Vignette du fichier
978-3-642-23960-1_53_Chapter.pdf (906.19 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01571496 , version 1 (02-08-2017)

Licence

Paternité

Identifiants

Citer

Angeliki Skoura, Vasileios Megalooikonomou, Predrag R. Bakic, Andrew Maidment. Classifying Ductal Tree Structures Using Topological Descriptors of Branching. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.455-463, ⟨10.1007/978-3-642-23960-1_53⟩. ⟨hal-01571496⟩
70 Consultations
75 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More