Computerized brain atlases as decision support systems: a methodological approach

Gibaud, Bernard; Garlatti, Serge; Barillot, Christian; Faure, Emmanuel

doi:10.1016/s0933-3657(98)00017-7

Cited by 15 publications

(9 citation statements)

References 33 publications

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“…Increasing amounts of information can be obtained with digital models available from brain atlases, thus facilitating the communication within research laboratories or within healthcare systems and integrated educational programs, through local and global networks [11,12,13,20,21]. In the field of image-guided neurosurgery, sulcal information has proven to be very helpful both in supporting the simulation of surgical situations and in the rehearsal of interventions [18,19].…”

Section: Discussionmentioning

confidence: 99%

“…The usefulness of these atlas systems in clinical decision support depends on how closely the brain of individual subjects matches the representation of anatomy in the atlas. Indeed, this method does not take into account the great inter-individual variability of the sulco-gyral anatomy [12,36,39,41]. Moreover, a part of the knowledge is represented in an implicit way, i.e., within the images.…”

Section: Introductionmentioning

confidence: 99%

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Numeric and symbolic knowledge representation of cerebral cortex anatomy: methods and preliminary results

Dameron

Gibaud

Morandi

2004

Surgical and Radiologic Anatomy

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The human cerebral cortex anatomy describes the brain organization at the scale of gyri and sulci. It is used as landmarks for neurosurgery as well as localization support for functional data analysis or inter-subject data comparison. Existing models of the cortex anatomy either rely on image labeling but fail to represent variability and structural properties or rely on a conceptual model but miss the inner 3D nature and relations of anatomical structures. This study was therefore conducted to propose a model of sulco-gyral anatomy for the healthy human brain. We hypothesized that both numeric knowledge (i.e., image-based) and symbolic knowledge (i.e., concept-based) have to be represented and coordinated. In addition, the representation of this knowledge should be application-independent in order to be usable in various contexts. Therefore, we devised a symbolic model describing specialization, composition and spatial organization of cortical anatomical structures. We also collected numeric knowledge such as 3D models of shape and shape variation about cortical anatomical structures. For each numeric piece of knowledge, a companion file describes the concept it refers to and the nature of the relationship. Demonstration software performs a mapping between the numeric and the symbolic aspects for browsing the knowledge base.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numeric and symbolic knowledge representation of cerebral cortex anatomy: methods and preliminary results

Dameron

Gibaud

Morandi

2004

Surgical and Radiologic Anatomy

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“…Such a registration allows to build an anatomical atlas of the cortex. Atlases such as [13,17] appear to be inadequate (legibility, capacity to evolve, difficulty of interpretation [8]). The major problem in building an atlas is the important variability of the human brain.…”

Section: Contextmentioning

confidence: 99%

Medical Image Registration with Robust Multigrid Techniques

Hellier

Barillot

Mémin

et al. 1999

Medical Image Computing and Computer-Assisted Intervention – MICCAI’99

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Abstract. In this paper we describe a new method of medical image registration based on robust estimators. We propose a general hierarchical optimization framework which is both multiresolution and multigrid with an adaptative partition of the volume. The approach may easily be adapted to different similarity measures (optical flow, mutual information or correlation ratio for instance) and may therefore be used either for mono-modality or for multi-modality registration. Here, we concentrate on the estimation of the optical flow leading to a single-modality non-linear registration. We aim at registering two MRI volumes of two different subjects. Results on real data are presented and discussed. Since this work is in progress, we expect more attractive and extensive results for the time of the conference.

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“…fMRI, PET, MEG/EEG) observations with a priori knowledge about brain anatomy and function. Representing this knowledge and implementing tools achieving this matching [1] usually rely on specific and ad hoc approaches, leading to a significant duplication of effort. Today, the progress of communication infrastructures and techniques, and particularly the Internet, enables a widespread sharing and reuse of data and knowledge, by both humans and machines, through platform-independent interfaces (e.g.…”

Section: Introductionmentioning

confidence: 99%

Implementation of atlas-matching capabilities using “web services” technology: Lessons learned from the development of a demonstrator

Gibaud

Dameron

Poiseau

et al. 2005

International Congress Series

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In this paper, we propose an approach for sharing data processing functions such as image to atlas registration and matching, based on platform-independent interfaces called bweb servicesQ. A prototype implementing this concept is described, enabling a user to match image data, e.g. MRI, to the Talairach atlas, as well as to 3D-data atlases such as the Statistical Probability Anatomy Maps (SPAM) datasets developed by the Montréal Neurological Institute (MNI). We emphasize architectural issues rather than functional aspects, which we consider classical. D 2005 Published by Elsevier B.V.

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Computerized brain atlases as decision support systems: a methodological approach

Cited by 15 publications

References 33 publications

Numeric and symbolic knowledge representation of cerebral cortex anatomy: methods and preliminary results

Numeric and symbolic knowledge representation of cerebral cortex anatomy: methods and preliminary results

Medical Image Registration with Robust Multigrid Techniques

Implementation of atlas-matching capabilities using “web services” technology: Lessons learned from the development of a demonstrator

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