Cortical sulci model and matching from 3D brain magnetic resonance images

Langlois, Serge; Royackkers, Nicolas; Fawal, Houssam; Desvignes, Michel; Revenu, Marinette; Travère, J.-M.

doi:10.1049/cp:19950633

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“…The sulcal labeling methods are also introduced by ChanWei Cnang et a1. [4] and S. Langlois et al [5]. Their methods can mathematically represent complex sulcal structure such as core, deep branches and fiber bundles.…”

Section: Introductionmentioning

confidence: 99%

MAGNET: an active ditch extraction model

Hirano

Kamiura²,

Hata³

et al.

Proceedings of International Conference on Image Processing

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T h i s paper presents a novel model t o detect the deepest point of a ditch as cerebral sulcus. Our model demonstrates magnetic behavior and consists of f o u r ideal magnetic poles: a n N-pole and three S-poles. D u e t o their Coulomb forces as the inverse square of the distance, one of S-poles automatically reaches the deepest point of the ditch. This model can also detect the point in case of ditch with implicit branches. Our experimental results o n sliced h u m a n brain M R images show that our method can detect the points a t 90% correct detection ratio.

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Section: Introductionmentioning

confidence: 99%