Analyse systématique et permanente de la délinquance sérielle : place des statistiques criminelles ; apport des approches situationnelles pour un système de classification ; perspectives en matière de coopération

Résumé de la thèse L'évolution des systèmes policiers donne une place prépondérante à l'information et au renseignement. Cette transformation implique de développer et de maintenir un ensemble de processus permanent d'analyse de la criminalité, en particulier pour traiter des événements répétitifs ou graves. Dans une organisation aux ressources limitées, le temps consacré au recueil des données, à leur codification et intégration, diminue le temps disponible pour l'analyse et la diffusion de renseignements. Les phases de collecte et d'intégration restent néanmoins indispensables, l'analyse n'étant pas possible sur des données volumineuses n'ayant aucune structure. Jusqu'à présent, ces problématiques d'analyse ont été abordées par des approches essentiellement spécialisées (calculs de hot-sports, data mining, ...) ou dirigées par un seul axe (par exemple, les sciences comportementales). Cette recherche s'inscrit sous un angle différent, une démarche interdisciplinaire a été adoptée. L'augmentation continuelle de la quantité de données à analyser tend à diminuer la capacité d'analyse des informations à disposition. Un bon découpage (classification) des problèmes rencontrés permet de délimiter les analyses sur des données pertinentes. Ces classes sont essentielles pour structurer la mémoire du système d'analyse. Les statistiques policières de la criminalité devraient déjà avoir répondu à ces questions de découpage de la délinquance (classification juridique). Cette décomposition a été comparée aux besoins d'un système de suivi permanent dans la criminalité. La recherche confirme que nos efforts pour comprendre la nature et la répartition du crime se butent à un obstacle, à savoir que la définition juridique des formes de criminalité n'est pas adaptée à son analyse, à son étude. Depuis près de vingt ans, les corps de police de Suisse romande utilisent et développent un système de classification basé sur l'expérience policière (découpage par phénomène). Cette recherche propose d'interpréter ce système dans le cadre des approches situationnelles (approche théorique) et de le confronter aux données « statistiques » disponibles pour vérifier sa capacité à distinguer les formes de criminalité. La recherche se limite aux cambriolages d'habitations, un délit répétitif fréquent. La théorie des opportunités soutien qu'il faut réunir dans le temps et dans l'espace au minimum les trois facteurs suivants : un délinquant potentiel, une cible intéressante et l'absence de gardien capable de prévenir ou d'empêcher le passage à l'acte. Ainsi, le délit n'est possible que dans certaines circonstances, c'est-à-dire dans un contexte bien précis. Identifier ces contextes permet catégoriser la criminalité. Chaque cas est unique, mais un groupe de cas montre des similitudes. Par exemple, certaines conditions avec certains environnements attirent certains types de cambrioleurs. Deux hypothèses ont été testées. La première est que les cambriolages d'habitations ne se répartissent pas uniformément dans les classes formées par des « paramètres situationnels » ; la deuxième que des niches apparaissent en recoupant les différents paramètres et qu'elles correspondent à la classification mise en place par la coordination judiciaire vaudoise et le CICOP. La base de données vaudoise des cambriolages enregistrés entre 1997 et 2006 par la police a été utilisée (25'369 cas). Des situations spécifiques ont été mises en évidence, elles correspondent aux classes définies empiriquement. Dans une deuxième phase, le lien entre une situation spécifique et d'activité d'un auteur au sein d'une même situation a été vérifié. Les observations réalisées dans cette recherche indiquent que les auteurs de cambriolages sont actifs dans des niches. Plusieurs auteurs sériels ont commis des délits qui ne sont pas dans leur niche, mais le nombre de ces infractions est faible par rapport au nombre de cas commis dans la niche. Un système de classification qui correspond à des réalités criminelles permet de décomposer les événements et de mettre en place un système d'alerte et de suivi « intelligent ». Une nouvelle série dans un phénomène sera détectée par une augmentation du nombre de cas de ce phénomène, en particulier dans une région et à une période donnée. Cette nouvelle série, mélangée parmi l'ensemble des délits, ne serait pas forcément détectable, en particulier si elle se déplace. Finalement, la coopération entre les structures de renseignement criminel opérationnel en Suisse romande a été améliorée par le développement d'une plateforme d'information commune et le système de classification y a été entièrement intégré.

Functional mapping of the human visual cortex with intravoxel incoherent motion MRI.

Functional imaging with intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) is demonstrated. Images were acquired at 3 Tesla using a standard Stejskal-Tanner diffusion-weighted echo-planar imaging sequence with multiple b-values. Cerebro-spinal fluid signal, which is highly incoherent, was suppressed with an inversion recovery preparation pulse. IVIM microvascular perfusion parameters were calculated according to a two-compartment (vascular and non-vascular) diffusion model. The results obtained in 8 healthy human volunteers during visual stimulation are presented. The IVIM blood flow related parameter fD* increased 170% during stimulation in the visual cortex, and 70% in the underlying white matter.

Quantitative Measurement of Brain Perfusion with Intravoxel Incoherent Motion MR Imaging.

Purpose: To evaluate the sensitivity of the perfusion parameters derived from Intravoxel Incoherent Motion (IVIM) MR imaging to hypercapnia-induced vasodilatation and hyperoxygenation-induced vasoconstriction in the human brain. Materials and Methods: This study was approved by the local ethics committee and informed consent was obtained from all participants. Images were acquired with a standard pulsed-gradient spin-echo sequence (Stejskal-Tanner) in a clinical 3-T system by using 16 b values ranging from 0 to 900 sec/mm(2). Seven healthy volunteers were examined while they inhaled four different gas mixtures known to modify brain perfusion (pure oxygen, ambient air, 5% CO(2) in ambient air, and 8% CO(2) in ambient air). Diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), and blood flow-related parameter (fD*) maps were calculated on the basis of the IVIM biexponential model, and the parametric maps were compared among the four different gas mixtures. Paired, one-tailed Student t tests were performed to assess for statistically significant differences. Results: Signal decay curves were biexponential in the brain parenchyma of all volunteers. When compared with inhaled ambient air, the IVIM perfusion parameters D*, f, and fD* increased as the concentration of inhaled CO(2) was increased (for the entire brain, P = .01 for f, D*, and fD* for CO(2) 5%; P = .02 for f, and P = .01 for D* and fD* for CO(2) 8%), and a trend toward a reduction was observed when participants inhaled pure oxygen (although P > .05). D remained globally stable. Conclusion: The IVIM perfusion parameters were reactive to hyperoxygenation-induced vasoconstriction and hypercapnia-induced vasodilatation. Accordingly, IVIM imaging was found to be a valid and promising method to quantify brain perfusion in humans. © RSNA, 2012.

Lipid composition of fingermark residue and donor classification using GC/MS

Lipids available in fingermark residue represent important targets for enhancement and dating techniques. While it is well known that lipid composition varies among fingermarks of the same donor (intra-variability) and between fingermarks of different donors (inter-variability), the extent of this variability remains uncharacterised. Thus, this worked aimed at studying qualitatively and quantitatively the initial lipid composition of fingermark residue of 25 different donors. Among the 104 detected lipids, 43 were reported for the first time in the literature. Furthermore, palmitic acid, squalene, cholesterol, myristyl myristate and myristyl myristoleate were quantified and their correlation within fingermark residue was highlighted. Ten compounds were then selected and further studied as potential targets for dating or enhancement techniques. It was shown that their relative standard deviation was significantly lower for the intra-variability than for the inter-variability. Moreover, the use of data pretreatments could significantly reduce this variability. Based on these observations, an objective donor classification model was proposed. Hierarchical cluster analysis was conducted on the pre-treated data and the fingermarks of the 25 donors were classified into two main groups, corresponding to "poor" and "rich" lipid donors. The robustness of this classification was tested using fingermark replicates of selected donors. 86% of these replicates were correctly classified, showing the potential of such a donor classification model for research purposes in order to select representative donors based on compounds of interest.

Central and Cortical Gray Mater Segmentation of Magnetic Resonance Images of the Fetal Brain

Motivation. The study of human brain development in itsearly stage is today possible thanks to in vivo fetalmagnetic resonance imaging (MRI) techniques. Aquantitative analysis of fetal cortical surfacerepresents a new approach which can be used as a markerof the cerebral maturation (as gyration) and also forstudying central nervous system pathologies [1]. However,this quantitative approach is a major challenge forseveral reasons. First, movement of the fetus inside theamniotic cavity requires very fast MRI sequences tominimize motion artifacts, resulting in a poor spatialresolution and/or lower SNR. Second, due to the ongoingmyelination and cortical maturation, the appearance ofthe developing brain differs very much from thehomogenous tissue types found in adults. Third, due tolow resolution, fetal MR images considerably suffer ofpartial volume (PV) effect, sometimes in large areas.Today extensive efforts are made to deal with thereconstruction of high resolution 3D fetal volumes[2,3,4] to cope with intra-volume motion and low SNR.However, few studies exist related to the automatedsegmentation of MR fetal imaging. [5] and [6] work on thesegmentation of specific areas of the fetal brain such asposterior fossa, brainstem or germinal matrix. Firstattempt for automated brain tissue segmentation has beenpresented in [7] and in our previous work [8]. Bothmethods apply the Expectation-Maximization Markov RandomField (EM-MRF) framework but contrary to [7] we do notneed from any anatomical atlas prior. Data set &Methods. Prenatal MR imaging was performed with a 1-Tsystem (GE Medical Systems, Milwaukee) using single shotfast spin echo (ssFSE) sequences (TR 7000 ms, TE 180 ms,FOV 40 x 40 cm, slice thickness 5.4mm, in plane spatialresolution 1.09mm). Each fetus has 6 axial volumes(around 15 slices per volume), each of them acquired inabout 1 min. Each volume is shifted by 1 mm with respectto the previous one. Gestational age (GA) ranges from 29to 32 weeks. Mother is under sedation. Each volume ismanually segmented to extract fetal brain fromsurrounding maternal tissues. Then, in-homogeneityintensity correction is performed using [9] and linearintensity normalization is performed to have intensityvalues that range from 0 to 255. Note that due tointra-tissue variability of developing brain someintensity variability still remains. For each fetus, ahigh spatial resolution image of isotropic voxel size of1.09 mm is created applying [2] and using B-splines forthe scattered data interpolation [10] (see Fig. 1). Then,basal ganglia (BS) segmentation is performed on thissuper reconstructed volume. Active contour framework witha Level Set (LS) implementation is used. Our LS follows aslightly different formulation from well-known Chan-Vese[11] formulation. In our case, the LS evolves forcing themean of the inside of the curve to be the mean intensityof basal ganglia. Moreover, we add local spatial priorthrough a probabilistic map created by fitting anellipsoid onto the basal ganglia region. Some userinteraction is needed to set the mean intensity of BG(green dots in Fig. 2) and the initial fitting points forthe probabilistic prior map (blue points in Fig. 2). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed as described in [8]. Results.The case study presented here has 29 weeks of GA. Thehigh resolution reconstructed volume is presented in Fig.1. The steps of BG segmentation are shown in Fig. 2.Overlap in comparison with manual segmentation isquantified by the Dice similarity index (DSI) equal to0.829 (values above 0.7 are considered a very goodagreement). Such BG segmentation has been applied on 3other subjects ranging for 29 to 32 GA and the DSI hasbeen of 0.856, 0.794 and 0.785. Our segmentation of theinner (red and blue contours) and outer cortical surface(green contour) is presented in Fig. 3. Finally, torefine the results we include our WM segmentation in theFreesurfer software [12] and some manual corrections toobtain Fig.4. Discussion. Precise cortical surfaceextraction of fetal brain is needed for quantitativestudies of early human brain development. Our workcombines the well known statistical classificationframework with the active contour segmentation forcentral gray mater extraction. A main advantage of thepresented procedure for fetal brain surface extraction isthat we do not include any spatial prior coming fromanatomical atlases. The results presented here arepreliminary but promising. Our efforts are now in testingsuch approach on a wider range of gestational ages thatwe will include in the final version of this work andstudying as well its generalization to different scannersand different type of MRI sequences. References. [1]Guibaud, Prenatal Diagnosis 29(4) (2009). [2] Rousseau,Acad. Rad. 13(9), 2006, [3] Jiang, IEEE TMI 2007. [4]Warfield IADB, MICCAI 2009. [5] Claude, IEEE Trans. Bio.Eng. 51(4) (2004). [6] Habas, MICCAI (Pt. 1) 2008. [7]Bertelsen, ISMRM 2009 [8] Bach Cuadra, IADB, MICCAI 2009.[9] Styner, IEEE TMI 19(39 (2000). [10] Lee, IEEE Trans.Visual. And Comp. Graph. 3(3), 1997, [11] Chan, IEEETrans. Img. Proc, 10(2), 2001 [12] Freesurfer,http://surfer.nmr.mgh.harvard.edu.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Multilevel oblique corpectomy for cervical spondylotic myelopathy preserves segmental motion.

PURPOSE: To document the neurological outcome, spinal alignment and segmental range of movement after oblique cervical corpectomy (OCC) for cervical compressive myelopathy. METHODS: This retrospective study included 109 patients--93 with cervical spondylotic myelopathy and 16 with ossified posterior longitudinal ligament in whom spinal curvature and range of segmental movements were assessed on neutral and dynamic cervical radiographs. Neurological function was measured by Nurick's grade and modified Japanese Orthopedic Association (JOA) scores. Eighty-eight patients (81%) underwent either a single- or two-level corpectomy; the remaining (19%) undergoing three- or four-level corpectomies. The average duration of follow-up was 30.52 months. RESULTS: The Nurick's grade and the JOA scores showed statistically significant improvements after surgery (p < 0.001). The mean postoperative segmental angle in the neutral position straightened by 4.7 ± 6.5°. The residual segmental range of movement for a single-level corpectomy was 16.7° (59.7% of the preoperative value), for two-level corpectomy it was 20.0° (67.2%) and for three-level corpectomies it was 22.9° (74.3%). 63% of patients with lordotic spines continued to have lordosis postoperatively while only one became kyphotic without clinical worsening. Four patients with preoperative kyphotic spines showed no change in spine curvature. None developed spinal instability. CONCLUSIONS: The OCC preserves segmental motion in the short-term, however, the tendency towards straightening of the spine, albeit without clinical worsening, warrants serial follow-up imaging to determine whether this motion preservation is long lasting.

Dependence of brain intravoxel incoherent motion perfusion parameters on the cardiac cycle.

Measurement of microvascular perfusion with Intravoxel Incoherent Motion (IVIM) MRI is gaining interest. Yet, the physiological influences on the IVIM perfusion parameters ("pseudo-diffusion" coefficient D*, perfusion fraction f, and flow related parameter fD*) remain insufficiently characterized. In this article, we hypothesize that D* and fD*, which depend on blood speed, should vary during the cardiac cycle. We extended the IVIM model to include time dependence of D* = D*(t), and demonstrate in the healthy human brain that both parameters D* and fD* are significantly larger during systole than diastole, while the diffusion coefficient D and f do not vary significantly. The results non-invasively demonstrate the pulsatility of the brain's microvasculature.

International consensus conference on PFAPA syndrome: evaluation of a new set of classification criteria

INTRODUCTION: PFAPA syndrome is characterized by periodic fever, associated with pharyngitis, cervical adenitis and/or aphthous stomatitis and belongs to the auto-inflammatory diseases. Diagnostic criteria are based on clinical features and the exclusion of other periodic fever syndromes. An analysis of a large cohort of patients has shown weaknesses for these criteria and there is a lack of international consensus. An International Conference was held in Morges in November 2008 to propose a new set of classification criteria based on a consensus among experts in the field.OBJECTIVE: We aimed to verify the applicability of the new set of classification criteria.PATIENTS & METHODS: 80 patients diagnosed with PFAPA syndrome from 3 centers (Genoa, Lausanne and Geneva) for pediatric rheumatology were included in the study. A detailed description of the clinical and laboratory features was obtained. The new classification criteria and the actual diagnostic criteria were applied to the patients.RESULTS: Only 40/80 patients (50%) fulfilled all criteria of the new classification. 31 patients were excluded because they didn't meet one of the 7 diagnostic criteria, 7 because of 2 criteria, and one because of 3 criteria. When we applied the current criteria to the same patients, 11/80 patients (13.7%) needed to be excluded. 8/80 patients (10%) were excluded from both sets. Exclusion was related only to some of the criteria. Number of patients for each not fulfilled criterion (new set of criteria/actual criteria): age (1/6), symptoms between episodes (2/2), delayed growth (4/1), main symptoms (21/0), periodicity, length of fever, interval between episodes, and length of disease (20/0). The application of some of the new criteria was not easy, as they were both very restrictive and needed precise information from the patients.CONCLUSION: Our work has shown that the new set of classification criteria can be applied to patients suspected for PFAPA syndrome, but it seems to be more restrictive than the actual diagnostic criteria. A further work of validation needs to be done in order to determine if this new set of classification criteria allow a good discrimination between PFAPA patients and other causes of recurrent fever syndromes.

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.