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Conference Papers Year : 2012

Vascular network segmentation: an unsupervised approach

Abstract

Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We consider a partition of the volume obtained by a watershed algorithm based on the distance from the nearest vessel. Each territory is characterized by its volume and the local vascular density. The volume and density maps are first regularized by minimizing the total variation. Then, a new approach is proposed to segment the volume from the two previous restored images based on hypothesis testing. Results are presented on 3D micro-tomographic images of the brain micro-vascular network.
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Dates and versions

hal-04023461 , version 1 (10-03-2023)

Identifiers

  • HAL Id : hal-04023461 , version 1
  • OATAO : 9193

Cite

Xavier Descombes, Franck Plouraboué, Abdelhakim El Boustani, Caroline Fonta, Géraldine Le Duc, et al.. Vascular network segmentation: an unsupervised approach. ISBI 2012 - 9th IEEE International Symposium on Biomedical Imaging, May 2012, Barcelona, Spain. pp.1248-1251. ⟨hal-04023461⟩
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