Using multimodal MR data for segmentation and topology recovery of the cerebral superficial venous tree

Nicolas Passat 1, 2 Christian Ronse 1 Joseph Baruthio 2 Jean-Paul Armspach 2 Marcel Bosc 3 Jack Foucher 4
1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 LNV - Laboratoire de Neuroimagerie in Vivo
3 L2TI - Laboratoire de Traitement et Transport de l'Information
4 Laboratoire de Psychopathologie et de Pharmacologie de la Cognition
Abstract : Magnetic resonance angiography (MRA) produces 3D data visualizing vascular structures by detecting the flowing blood signal. While segmentation methods generally detect vessels by only processing MRA, the proposed method uses both MRA and non-angiographic (MRI) images. It is based on the assumption that MRI provides anatomical information useful for vessel detection. This supplementary information can be used to correct the topology of the segmented vessels. Vessels are first segmented from MRA while the cortex is segmented from MRI. An algorithm, based on distance maps and topology preserving thinning , then uses both segmented structures for recovery of the missing parts of the brain superficial venous tree and removal of other vessels. This method has been performed and validated on 9 MRA/MRI data of the brain. The results show that the venous tree is correctly segmented and topologically recovered with a 84% accuracy.
Document type :
Conference papers
Complete list of metadatas

Cited literature [10 references]  Display  Hide  Download
https://hal.univ-reims.fr/hal-01694970
Contributor : Nicolas Passat <>
Submitted on : Wednesday, January 31, 2018 - 4:23:34 PM
Last modification on : Thursday, February 7, 2019 - 5:48:52 PM
Long-term archiving on : Friday, May 25, 2018 - 5:08:54 PM

File

Draft.pdf
Files produced by the author(s)

Identifiers

Collections

URCA | UNIV-PARIS13 | CNRS | L2TI | USPC | GALILE

Citation

Nicolas Passat, Christian Ronse, Joseph Baruthio, Jean-Paul Armspach, Marcel Bosc, et al.. Using multimodal MR data for segmentation and topology recovery of the cerebral superficial venous tree. International Symposium on Visual Computing (ISVC), 2005, Lake Tahoe, United States. pp.60-67, ⟨10.1007/11595755_8⟩. ⟨hal-01694970⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

196

Files downloads

373

 

HAL-contact@univ-reims.fr