Biomedical subjects

Sébastien Ourselin

Publications and source records attributed to Sébastien Ourselin.

5 recordsLinked to original sources

PubMed2006

A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data.

This paper describes the construction of an atlas of the human basal ganglia. The successive steps of the construction were as follows. First a postmortem specimen was subjected to a MRI acquisition prior to extraction of the brain from the skull. The brain was then cryosectioned (70 microm thickness). One section out of ten (80 sections) was Nissl-stained with cresyl violet, another series of 80 sections was immunostained for the calcium binding protein calbindin. Contours of basal ganglia nuclei including their calbindin-stained functional subdivisions, fiber bundles and ventricles (n=80 structures) were traced from histological sections and digitized. A novelty of this atlas is the MRI acquisition, which represents the core data element of the study. MRI was used for the coregistration of the atlas data and permitted, through multimodal (Nissl, calbindin, images of cryosectioning, T1 and T2 MRI) and 3D optimization, the production of anatomically and geometrically consistent 3D surfaces, which can be sliced through any desired orientation. The atlas MRI is also used for its deformation to provide accurate conformation to the MRI of living patients, thus adding information at the histological level to the patient's MRI volume. This latter aspect will be presented in a forthcoming paper.

Basal Ganglia↗

PubMed2006

Efficient topology modification and deformation for finite element models using condensation.

Cuts on deformable organs are a central task in the set of physical operations needed in many surgical simulation environments. Our BioMedIA surgical simulator structures are Finite Element Models, driven by displacements on the touched nodes as opposed to forces. This approach allows for realistic simulation of both deformation and haptic response at real-time rates. The integration of condensation into our system increases its efficiency, and allows for complex interaction on larger meshes than would normally be permitted with available memory. We present an extension of our novel algorithm for cuts in deformable organs, in the context of condensed matrices. We show results from our surgical simulation system with real-time haptic feedback.

Algorithms↗

PubMed2005

Multiple contact approach to collision modelling in surgical simulation.

In this paper we present a technique for the modelling of realistic collisions between arbitrary rigid surgical tools and deformable geometry that is independent of the resolution of colliding objects. We use a spatial hash table to provide an efficient narrow-phase collision detection and modelling backend. This is combined with previous work on collision modelling in our surgical simulation environment to model realistic collisions and collision response at haptic rates.

Australia↗

PubMed2005

The use of unwrapped phase in MR image segmentation: a preliminary study.

This paper considers the problem of tissue classification in 3D MRI. More specifically, a new set of texture features, based on phase information, is used to perform the segmentation of the bones of the knee. The phase information provides a very good discrimination between the bone and the surrounding tissues, but is usually not used due to phase unwrapping problems. We present a method to extract textural information from the phase that does not require phase unwrapping. The textural information extracted from the magnitude and the phase can be combined to perform tissue classification, and used to initialise an active shape model, leading to a more precise segmentation.

Algorithms↗

PubMed2002

Computation of the mid-sagittal plane in 3-D brain images.

We present a new method to automatically compute, reorient, and recenter the mid-sagittal plane in anatomical and functional three-dimensional (3-D) brain images. This iterative approach is composed of two steps. At first, given an initial guess of the mid-sagittal plane (generally, the central plane of the image grid), the computation of local similarity measures between the two sides of the head allows to identify homologous anatomical structures or functional areas, by way of a block matching procedure. The output is a set of point-to-point correspondences: the centers of homologous blocks. Subsequently, we define the mid-sagittal plane as the one best superposing the points on one side and their counterparts on the other side by reflective symmetry. Practically, the computation of the parameters characterizing the plane is performed by a least trimmed squares estimation. Then, the estimated plane is aligned with the center of the image grid, and the whole process is iterated until convergence. The robust estimation technique we use allows normal or abnormal asymmetrical structures or areas to be treated as outliers, and the plane to be mainly computed from the underlying gross symmetry of the brain. The algorithm is fast and accurate, even for strongly tilted heads, and even in presence of high acquisition noise and bias field, as shown on a large set of synthetic data. The algorithm has also been visually evaluated on a large set of real magnetic resonance (MR) images. We present a few results on isotropic as well as anisotropic anatomical (MR and computed tomography) and functional (single photon emission computed tomography and positron emission tomography) real images, for normal and pathological subjects.

Algorithms↗