A generic framework for the parcellation of the cortical surface into gyri using geodesic Voronoı̈ diagrams

Cachia, Arnaud; Mangin, Jean‐François; Rivière, Denis; Papadopoulos‐Orfanos, Dimitri; Kherif, Ferath; Bloch, Isabelle; Régis, Jean

doi:10.1016/s1361-8415(03)00031-8

Cited by 99 publications

(77 citation statements)

References 46 publications

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“…The central surface, in particular, demonstrates accuracy and repeatability in the range of 0.5 and 0.25 mm, respectively. We believe that the central surface is useful for characterization and analysis of the 2-D geometry of the cortex-for example, computation of curvatures (Cachia et al, 2003a;Zeng et al, 1999), geodesic distances (Cachia et al, 2003b;Rettmann et al, 2002), segmenting sulci or gyri (Behnke et al, 2003;Cachia et al, 2003b;Rettmann et al, 2002), surface flattening (Carman et al, 1995;Drury et al, 1996), and spherical mapping (Angenent et al, 1999;Fischl et al, 1999a;Tosun and Prince, 2001).…”

Section: Qualitative Demonstrationsmentioning

confidence: 99%

CRUISE: Cortical reconstruction using implicit surface evolution

et al. 2004

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Segmentation and representation of the human cerebral cortex from magnetic resonance (MR) images play an important role in neuroscience and medicine. A successful segmentation method must be robust to various imaging artifacts and produce anatomically meaningful and consistent cortical representations. A method for the automatic reconstruction of the inner, central, and outer surfaces of the cerebral cortex from T1-weighted MR brain images is presented. The method combines a fuzzy tissue classification method, an efficient topology correction algorithm, and a topology-preserving geometric deformable surface model (TGDM). The algorithm is fast and numerically stable, and yields accurate brain surface reconstructions that are guaranteed to be topologically correct and free from selfintersections. Validation results on real MR data are presented to demonstrate the performance of the method. D 2004 Elsevier Inc. All rights reserved.

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Section: Qualitative Demonstrationsmentioning

confidence: 99%

CRUISE: Cortical reconstruction using implicit surface evolution

et al. 2004

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“…The pattern of a sulcus, even a major one, can have a different shape or different topology from one brain to another. One of the reasons of this variability is thought to be the result of the cortex folding process [11,2,16,14]. To provide invariant features, we have to understand the sulci organization over the cortical surface [8,16,14].…”

Section: Anatomical Backgroundmentioning

confidence: 99%

“…Hence, if a fold is considered to be a longitude constraint, it cannot and will not be used as a latitude constraint. The correlation between sulcal-based representation and gyral-based representation has been established by [2]. In this context, sulci are considered as indicators of the meeting lines buried in the fold's depth between the two neighboring gyri.…”

Section: Anatomical Backgroundmentioning

confidence: 99%

Anatomically Constrained Surface Parameterization for Cortical Localization

Clouchoux¹,

Coulon²,

Rivière³

et al. 2005

Lecture Notes in Computer Science

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Abstract. We present here a method that aims at defining a surfacebased coordinate system on the cortical surface. Such a system is needed for both cortical localization and intersubject matching in the framework of neuroimaging. We propose an automatic parameterization based on the spherical topology of the grey/white matter interface of each hemisphere and on the use of naturally organized and reproducible anatomical features. From those markers used as initial constraints, the coordinate system is propagated via a PDE solved on the cortical surface.

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“…The annotation of images, in our case anatomical MRI images, has two objectives: 1) to help to identify precisely the gyri and sulci around the lesion, and to provide the detailed annotation data relating anatomical conceptual entities to graphical primitives extracted from the images; 2) to use these metadata for cases retrieval in an images database. Our approach significantly differs from classical approaches of parcellation of cortex in MRI images [4,5,6,7]. Those are generally global (i.e.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid System for the Semantic Annotation of Sulco-Gyral Anatomy in MRI Images

Mechouche

Morandi

Golbreich

et al. 2008

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008

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Abstract. This paper presents an interactive system for the annotation of brain anatomical structures in Magnetic Resonance Images. The system is based on hybrid knowledge and techniques. First, it exploits both numerical knowledge from atlases and symbolic knowledge from a ruleextended ontology represented in OWL, the Web ontology language, and combines them with graphical data about cortical sulci, automatically extracted from the images. Second, the annotations of the parts of gyri and of sulci located in a region of interest are obtained with different reasoning techniques: Constraint Satisfaction Solving and Description Logics techniques. Preliminary experiments have been achieved on normal and also pathological data. The results obtained so far are very promising.

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A generic framework for the parcellation of the cortical surface into gyri using geodesic Voronoı̈ diagrams

Cited by 99 publications

References 46 publications

CRUISE: Cortical reconstruction using implicit surface evolution

CRUISE: Cortical reconstruction using implicit surface evolution

Anatomically Constrained Surface Parameterization for Cortical Localization

A Hybrid System for the Semantic Annotation of Sulco-Gyral Anatomy in MRI Images

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