3D statistical facial reconstruction

The aim of craniofacial reconstruction is to produce a likeness of a face from the skull. Few works in computerized assisted facial reconstruction have been done in the past, due to poor machine performances and data availability, and major works are manually reconstructions. In this paper, we present an approach to build 3D statistical models of the skull and the face with soft tissues from the skull of one individual. Results on real data are presented and seem promising

Statistical skull models from 3D X-ray images

We present 2 statistical models of the skull and mandible built upon an elastic registration method of 3D meshes. The aim of this work is to relate degrees of freedom of skull anatomy, as static relations are of main interest for anthropology and legal medicine. Statistical models can effectively provide reconstructions together with statistical precision. In our applications, patient-specific meshes of the skull and the mandible are high-density meshes, extracted from 3D CT scans. All our patient-specific meshes are registrated in a subject-shared reference system using our 3D-to-3D elastic matching algorithm. Registration is based upon the minimization of a distance between the high density mesh and a shared low density mesh, defined on the vertexes, in a multi resolution approach. A Principal Component analysis is performed on the normalised registrated data to build a statistical linear model of the skull and mandible shape variation. The accuracy of the reconstruction is under the millimetre in the shape space (after rigid registration). Reconstruction errors for Scan data of tests individuals are below registration noise. To take in count the articulated aspect of the skull in our model, Kernel Principal Component Analysis is applied, extracting a non-linear parameter associated with mandible position, therefore building a statistical articulated 3D model of the skull.Comment: Proceedings of the Second International Conference on Reconstruction of Soft Facial Parts RSFP'200

Graph-based skin lesion segmentation of multispectral dermoscopic images

International audienceAccurate skin lesion segmentation is critical for automated early skin cancer detection and diagnosis. We present a novel method to detect skin lesion borders in multispectral der-moscopy images. First, hairs are detected on infrared images and removed by inpainting visible spectrum images. Second, skin lesion is pre-segmented using a clustering of a superpixel partition. Finally, the pre-segmentation is globally regular-ized at the superpixel level and locally regularized in a narrow band at the pixel level

New data model for graph-cut segmentation: application to automatic melanoma delineation

International audienceWe propose a new data model for graph-cut image segmentation, defined according to probabilities learned by a classification process. Unlike traditional graph-cut methods, the data model takes into account not only color but also texture and shape information. For melanoma images, we also introduce skin chromophore features and automatically derive "seed" pixels used to train the classifier from a coarse initial segmentation. On natural images, our method successfully segments objects having similar color but different texture. Its application to melanoma delineation compares favorably to manual delineation and related graph-cut segmentation methods

Morphometry and Identification of Brain Sulci on Three-Dimensional MR Images

International audiencePositron emission tomography (PET) is widely used for the study of human cerebral activity. As PET images do not reflect brain anatomy of pationts, functional areas identified in such examinations cannot be localized precisely. Thus, a matching between PET and anatomical data from other sources is necessary to make the most of PET images. An approach to this problem is the direct recognition of cortical sulci on 3D magnetic resonance images (MRI) in order to build an accurate parcellation of brain for the localization of functional areas found in PET examinations

Local order and magnetic behavior of amorphous and nanocrystalline yttrium iron garnet produced by swift heavy ion irradiations

International audienceThin epitaxial films of gallium or scandium-doped and undoped yttrium iron garnet (Y3Fe5O12 or YIG) on nonmagnetic Gd3Ga5O12 substrates were irradiated with swift heavy ions (50 MeV 32S, 50 MeV 63Cu, and 235 MeV 84Kr) in the electronic slowing down regime. The mean electronic stopping power in the films was always larger than the threshold for amorphous track formation in YIG which is around 4.5 MeV/μm in this low ion-velocity range. The local order and magnetic properties of the damaged films were then studied at room temperature by 57Fe conversion electron Mössbauer spectroscopy (CEMS) and x-ray absorption spectroscopy (XAS) at the iron K edge in the fluorescence mode. In the case of paramagnetic gallium or scandium-substituted films (YIG:Ga, YIG:Sc) irradiated with 32S or 63Cu ions, the CEMS data show that the tetrahedral Fe3+ sites are preferentially damaged, while the octahedral sites are conserved. This is confirmed by the decrease of the pre-edge peak in the XAS data of the ferrimagnetic undoped YIG films showing that the number of tetrahedral iron sites is decreased in the amorphous phase obtained with 84Kr ion irradiation, due to the formation of fivefold-coordinated pyramidal sites, as already found in a previous study on undoped YIG sinters amorphized by 3.5 GeV 132Xe ion irradiation. In the case of the nanophase induced by ion-beam recrystallization of the tracks with 32S or 63Cu irradiations, a further decrease of the pre-edge peak is found. This is interpreted by (i) an increase of the fivefold-coordinated pyramidal sites and/or (ii) a probable decomposition of the garnet into orthoferrite (YFeO3) and haematite (α-Fe2O3) under the high-pressure and high-temperature conditions in the thermal spike generated by the ions. The CEMS data of irradiated undoped YIG also show that both the amorphous and nanocrystalline phases have a paramagnetic behavior at room temperature. The nanophase magnetic behavior is analyzed on the basis of a superparamagnetic relaxation above the blocking temperature, whereas the amorphous phase behavior is ascribed to a speromagnetic state

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

International audiencePositron emission tomography (PET) is one of the most popular techniques for the study of brain functional activity. Several studies show that PET is an in-vivo examination technique able to produce real images of cerebral activity, and is also neither destructive nor invasive. Unfortunately, PET images offer low resolution and signal-to-noise ratio. Moreover, they do not reflect the anatomy of patients. Accurate and reproducible analysis of PET images requires other informations, coming from aliases or other images such as magnetic resonance images (MRI) of the same patient. Hence it is of great interest to superimpose functional PET data and anatomical MRI data. Here, the authors deal with representation and identification of sulci. A first step is to choose and to automatically extract anatomical knowledge from a database, in order to adapt it to any image where the recognition has to be performed. Then, the authors introduce a stochastic method using these features to recognise human cerebral sulci

Fusion individuelle de données cérébrales multimodales : informations issues d'images numériques et connaissances expertes

National audienceL'étude de l'activité fonctionnelle cérébrale à partir d'images TEP est difficile à cause de la résolution spatiale limitée et du faible rapport signal sur bruit de celles-ci. Cette étude nécessite l'utilisation conjointe et la fusion d'informations provenant de différentes modalités d'images numériques et de connaissances expertes modélisées dans des atlas. Ces derniers se rapportant à une anatomie standard, il est fondamental de les adapter auparavant à la morphologie spécifique du patient concerné. Pour résoudre au mieux les problèmes rencontrés depuis l'acquisition de l'image à l'identification des différentes zones, nous proposons dans cet article une méthodologie pour obtenir des données individualisées et pour les fusionner. La première étape fait intervenir un processus automatique de recalage de l'image TEP avec une image RM, via une radiographie par Rayons X, par l'introduction d'informations a priori extraites d'un atlas. La seconde étape vise à individualiser les atlas anatomiques pour que la superposition avec les images TEP soit plus précise. Dans cette optique, une méthode d'identification des sillons du cortex d'un patient sur une image RM 3D est présentée. L'accent est mis sur la généralité de la démarche, sur l'explicitation des connaissances et des mécanismes de fusion, et sur l'évaluation des résultats en fonction des images traitées