Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

Multispectral brain morphometry in Tourette syndrome persisting into adulthood.

Tourette syndrome is a childhood-onset neuropsychiatric disorder with a high prevalence of attention deficit hyperactivity and obsessive-compulsive disorder co-morbidities. Structural changes have been found in frontal cortex and striatum in children and adolescents. A limited number of morphometric studies in Tourette syndrome persisting into adulthood suggest ongoing structural alterations affecting frontostriatal circuits. Using cortical thickness estimation and voxel-based analysis of T1- and diffusion-weighted structural magnetic resonance images, we examined 40 adults with Tourette syndrome in comparison with 40 age- and gender-matched healthy controls. Patients with Tourette syndrome showed relative grey matter volume reduction in orbitofrontal, anterior cingulate and ventrolateral prefrontal cortices bilaterally. Cortical thinning extended into the limbic mesial temporal lobe. The grey matter changes were modulated additionally by the presence of co-morbidities and symptom severity. Prefrontal cortical thickness reduction correlated negatively with tic severity, while volume increase in primary somatosensory cortex depended on the intensity of premonitory sensations. Orbitofrontal cortex volume changes were further associated with abnormal water diffusivity within grey matter. White matter analysis revealed changes in fibre coherence in patients with Tourette syndrome within anterior parts of the corpus callosum. The severity of motor tics and premonitory urges had an impact on the integrity of tracts corresponding to cortico-cortical and cortico-subcortical connections. Our results provide empirical support for a patho-aetiological model of Tourette syndrome based on developmental abnormalities, with perturbation of compensatory systems marking persistence of symptoms into adulthood. We interpret the symptom severity related grey matter volume increase in distinct functional brain areas as evidence of ongoing structural plasticity. The convergence of evidence from volume and water diffusivity imaging strengthens the validity of our findings and attests to the value of a novel multimodal combination of volume and cortical thickness estimations that provides unique and complementary information by exploiting their differential sensitivity to structural change.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

Images in clinical urology. Nail of glans penis.

A 56-year-old man presented with a "nail" growing at the base of his glans penis. The tumor was locally excised, and microscopic examination revealed papillomatosis and hyperkeratosis of the malpighian epithelium, with a strong inflammatory reaction of the chorion and signs of local microinvasion, as well as the presence of well-differentiated squamous epithelial cells. The surgical margins were negative. The differential diagnosis was made between a benign papillomatous proliferation and verrucous carcinoma.

Détectabilité extra-fovéale sur des images anatomiques

Contexte¦- Les métastases hépatiques hypovasculaires sont parfois difficile à détecter car très polymorphiques et fréquemment irrégulières. Leurs contrastes sur CT scan hépatique sont souvent faibles.¦- Lors d'un diagnostic, le radiologue ne fixe pas sa vision fovéale sur chaque pixel de l'image. Les expériences de psychophysique avec eye-tracker montrent en effet que le radiologue se concentre sur quelques points spécifiques de l'image appelés fixations. Dans ce travail, nous nous intéresserons aux capacités de détection de l'oeil lorsque l'observateur effectue une saccade entre deux points de fixation. Plus particulièrement, nous nous intéresserons à caractériser les capacités de l'oeil à détecter les signaux se trouvant en dehors de sa vision fovéale, dans ce qu'on appelle, la vision périphérique.¦Objectifs¦- Caractériser l'effet de l'excentricité de la vision sur la détectabilité des contrastes dans le cas de métastases hépatiques hypovasculaires.¦- Récolter des données expérimentales en vue de créer un modèle mathématique qui permettra, à terme, de qualifier le système d'imagerie.¦- → objectifs du TM en soit :¦o prendre en main l'eyetracker¦o traduire une problématique médicale en une expérience scientifique reproductible, quantifiable et qualifiable.¦Méthode¦Nous effectuons une expérience 2AFC (2 Alternative Forced-Choice experiment) afin d'estimer la détectabilité du signal. Pour cela, nous forcerons l'observateur à maintenir son point de fixation à un endroit défini et vérifié par l'eye-tracker. La position del'excentricité du signal tumoral généré sur une coupe de CT hépatique sera le paramètre varié. L'observateur se verra présenté tour à tour deux coupes de CT hépatique, l'une comportant le signal tumoral standardisé et l'autre ne comportant pas le signal. L'observateur devra déterminer quelle image contient la pathologie avec la plus grande probabilité.¦- Cette expérience est un modèle simplifié de la réalité. En effet, le radiologue ne fixe pas un seul point lors de sa recherche mais effectue un "scanpath". Une seconde expérience, dite en free search sera effectuée dans la mesure du temps à disposition. Lors de cette expérience, le signal standardisé sera connu de l'observateur et il n'y aura plus de point de fixation forcée. L'eyetracker suivra le scanpath effectué par l'oeil de l'observateur lors de la recherche du signal sur une coupe de CT scan hépatique. L'intérêt de cette expérience réside dans l'observation de la corrélation entre les saccades et la découverte du signal. Elle permet aussi de vérifier les résultats obtenus lors de la première expérience.¦Résultats escomptés¦- Exp1 : Quantifier l'importance de l'excentricité en radiologie et aider à améliorer la performance de recherche.¦- Exp 2 : tester la validité des résultats obtenus par la première expérience.¦Plus value escomptée¦- Récolte de données pour créer un modèle mathématique capable de déterminer la qualité de l'image radiologique.¦- Possibilité d'extension à la recherche dans les trois dimensions du CT scan hépatique.

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.

Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature.

Extent of Hypoattenuation On CT Angiography Source Images In Basilar Artery Occlusion: Prognostic Accuracy Of Posterior Circulation ASPECTS And The Pons-midbrain Score In The Basilar Artery International Cooperation Study

Background: The posterior circulation Acute Stroke Prognosis Early CT Score (pc-ASPECTS) and the combined Pons-midbrain score quantify the extent of early ischemic changes in the posterior circulation. We compared the prognostic accuracy of both scores if applied to CT angiography (CTA) source images (CTA-SI) of patients in the Basilar Artery International Cooperation Study (BASICS).Methods: BASICS was a prospective, observational, multi-centre, registry of consecutive patients who presented with acute symptomatic basilar artery occlusion (BAO). Functional outcome was assessed at 1 month. We applied pc-ASPECTS and the combined Pons-midbrain score to CTA-SI by 3-reader-consensus. Readers were blinded to clinical data. We performed multivariable logistic regression analysis, adjusting for thrombolysis, baseline NIHSS score and age, and used the output to derive ROC curves to compare the ability of both scores to discriminate patients with favourable (modified Rankin Scale [mRS] scores 0-3) from patients with unfavourable (mRS scores 4-6) functional outcome.Results: We reviewed CTAs of 158 patients (64% men, mean age 65 _ 15 years, median NIHSS score 25 [0-38], median GCS score 7 [3-15], median onset-to-CTA time 234 minutes [11-7380]). At 1 month, 40 (25%) patients had a favourable outcome, 49 (31%) had an unfavourable outcome (mRS score 4-5) and 69 (44%) were deceased. Both techniques of assessing CTA-SI hypoattenuation in the posterior circulation showed equally good discriminative value in predicting final outcome (C-statistics; area under ROC curve 0.74 versus 0.75, respectively; p_0.37). Pc-ASPECTS dichotomized at _6 versus _6 was an independent predictor of favourable functional outcome (RR _ 2.2; CI95 1.1-4.7; p _ 0.034).Conclusion: Compared to the combined Pons-midbrain score, the pc-ASPECTS score has similar prognostic accuracy to identify patients with a favourable functional outcome in BASICS. Dichotomized pc-ASPECTS (_6 versus _6) is an independent predictor of favourable functional outcome in this population. Author Disclosures: V. Puetz: None. A. Khomenko: None. M.D. Hill: None. I. Dzialowski: None. P. Michel: None. C. Weimar: None. C.A.C. Wijman: None. H. Mattle: None. K. Muir: None. T. Pfefferkorn: None. D. Tanne: None. S. Engelter: None. K. Szabo: None. A. Algra: None. A.M. Demchuk: None. W.J. Schonewille: None.

Using the Number of Pores on Fingerprint Images to Detect Spoofing Attacks

Abstract-Due to the growing use of biometric technologies inour modern society, spoofing attacks are becoming a seriousconcern. Many solutions have been proposed to detect the use offake "fingerprints" on an acquisition device. In this paper, wepropose to take advantage of intrinsic features of friction ridgeskin: pores. The aim of this study is to investigate the potential ofusing pores to detect spoofing attacks.Results show that the use of pores is a promising approach. Fourmajor observations were made: First, results confirmed that thereproduction of pores on fake "fingerprints" is possible. Second,the distribution of the total number of pores between fake andgenuine fingerprints cannot be discriminated. Third, thedifference in pore quantities between a query image and areference image (genuine or fake) can be used as a discriminatingfactor in a linear discriminant analysis. In our sample, theobserved error rates were as follows: 45.5% of false positive (thefake passed the test) and 3.8% of false negative (a genuine printhas been rejected). Finally, the performance is improved byusing the difference of pore quantity obtained between adistorted query fingerprint and a non-distorted referencefingerprint. By using this approach, the error rates improved to21.2% of false acceptation rate and 8.3% of false rejection rate.