Model of Cortical Cell Processing to Estimate Binocular Disparity

International audienceThe starting point of our work are the physiological and psychophysical studies made on 3D vision, we attempt to build a model of stereoscopic vision. Hence, we used 2D Gabor filters to model the simple and complex cells sensitive to horizontal binocular disparity (Barlow 1967, Daugman 1985). Each of these cells has a preferred disparity and is sensitive to spatial frequency and orientation. It has been shown by Prince et al (2002) that the range of preferred disparities depends on the spatial frequency. We designed a bank of filters in which the distribution of preferred disparity follows the same principle. Moreover, since the stereo-threshold was found to be increasing with the magnitude of disparity inside each spatial frequency channel, the disparity distribution is not uniform. We took the energy model of Ohzawa et al (1986) as a basis since it has been demonstrated that it fits well with the disparity sensitive cells response from V1 in front of most of stimuli. We modified the classical model by normalizing the complex binocular response by the monocular complex response. We took different measures to reduce false matches such as a pooling procedure and an orientation averaging already used by Chen and Qian (2004). As already demonstrated for 2D vision, a coarse-to-fine process seems to be the best way to deal with multiple spatial frequency channels for stereoscopic vision (Smallman 1995, Menz and Freeman 2003). The first estimation based on low spatial frequencies determines if the estimation will be refined channels depending on its inclusion in the disparity range of the higher spatial frequency channel

Using natural versus artificial stimuli to perform calibration for 3D gaze tracking

International audienceThe presented study tests which type of stereoscopic image, natural or artificial, is more adapted to perform efficient and reliable calibration in order to track the gaze of observers in 3D space using classical 2D eye tracker. We measured the horizontal disparities, i.e. the difference between the x coordinates of the two eyes obtained using a 2D eye tracker. This disparity was recorded for each observer and for several target positions he had to fixate. Target positions were equally distributed in the 3D space, some on the screen (with a null disparity), some behind the screen (uncrossed disparity) and others in front of the screen (crossed disparity). We tested different regression models (linear and non linear) to explain either the true disparity or the depth with the measured disparity. Models were tested and compared on their prediction error for new targets at new positions. First of all, we found that we obtained more reliable disparities measures when using natural stereoscopic images rather than artificial. Second, we found that overall a non-linear model was more efficient. Finally, we discuss the fact that our results were observer dependent, with variability's between the observer's behavior when looking at 3D stimuli. Because of this variability, we proposed to compute observer specific model to accurately predict their gaze position when exploring 3D stimuli

Tracking a genetic signal of extinction-recolonization events in a neotropical tree species: Voucapoua americana Aublet in French Guiana

Drier periods from the late Pleistocene and early Holocene have been hypothesized to have caused the disappearance of various rainforest species over large geographical areas in South America and restricted the extant populations to mesic sites. Subsequent improvement in climatic conditions has been associated with recolonization. Changes in population size associated with these extinction‐recolonization events should have affected genetic diversity within species. However, these historical hypotheses and their genetic consequences have rarely been tested in South America. Here, we examine the diversity of the chloroplast and nuclear genomes in a Neotropical rainforest tree species, Vouacapoua americana (Leguminosae, Caesalpinioideae) in French Guiana. The chloroplast diversity was analyzed using a polymerase chain reaction‐restriction fragment length polymorphism method (six pairs of primers) in 29 populations distributed over most of French Guiana, and a subset of 17 populations was also analyzed at nine polymorphic microsatellite loci. To determine whether this species has experienced extinction‐recolonization, we sampled populations in areas supposedly not or only slightly affected by climatic changes, where the populations would not have experienced frequent extinction, and in areas that appear to have been recently recolonized. In the putatively recolonized areas, we found patches of several thousands of hectares homogeneous for chloroplast variation that can be interpreted as the effect of recolonization processes from several geographical origins. In addition, we observed that, for both chloroplast and nuclear genomes, the populations in newly recolonized areas exhibited a significantly smaller allelic richness than others. Controlling for geographic distance, we also detected a significant correlation between chloroplast and nuclear population differentiation. This result indicates a cytonuclear disequilibrium that can be interpreted as a historical signal of a genetic divergence between fragmented populations. In conclusion, the spatial genetic structure of contemporary V. americana populations shows evidence that this species has experienced large extinction‐recolonization events, which were possibly caused by past climatic change

De la rétine binoculaire aux premiers étages du cortex visuel pour la perception visuelle tridimensionnelle : modèle et expérimentations oculométriques

Depth vision or « 3D vision » can interpret tridimensional spatial relations between objects in a visual scene and gives humans a good precision of interaction with their environment. 3D vision uses several kinds of mechanisms to analyze visual signal. Some keep their power during a monocular stimulation (monocular depth cues) but others need a binocular stimulation (binocular depth cues). This thesis focuses on the binocular mechanism which uses the difference of point of view between the two eyes (also called retinal disparity). The work presented in this thesis follows two main approaches: the modeling of the retinal disparity extraction at the cortical level, and an experiment to analyze the influence of retinal disparity on visual attention during the exploration of natural stereoscopic scenes with eye tracking recording. The proposed model is built from physiologic data of primary visual cortex V1 found in the literature. Our model makes an estimation of the retinal disparity from modeled responses of simple and complex cells of V1. We take a bio-inspired approach at two levels. The first level concerns the global architecture of the organization and the interaction of cortical cells which extract the information at different spatial frequencies, orientations and disparities. The second level concerns the configuration of cortical cells implemented like spatial filters. The experimental part is subdivided into two parts. Indeed, the use of eye-tracking data of 3D scenes exploration needs a calibration step. Hence, we developed a 3D calibration method allowing us to track the depth of the gaze from the recorded binocular coordinates. Then, we analyze the influence of retinal disparity in the visual exploration of different categories of natural scenes based on the presence of monocular and binocular depth cues. The ocular dominance, the central bias and the depth bias are also studied in this paradigm. We show that a 2D saliency model is not adapted to predict the salient zone during 3D viewing but also during 2D viewing. The depth information must be integrated in saliency computation thanks to retinal disparity and monocular depth cues to explain fully the visual exploration both in 2D and 3D.La vision de la profondeur ou communément appelée « vision 3D » permet d'interpréter les relations spatiales tridimensionnelles entre les objets de la scène visuelle et confère à l'homme une grande précision dans ses interactions avec l'environnement. La vision 3D repose sur de nombreux mécanismes d'analyse du signal visuel dont la plupart gardent tout leur pouvoir informationnel lors de la stimulation d'un seul œil (indices monoculaires) mais dont certains nécessitent la stimulation des deux yeux (indices binoculaires). Cette thèse se concentre sur les mécanismes nécessitant les deux yeux qui mettent en jeu la différence de point de vue entre les deux yeux, aussi appelée disparité rétinienne. Les travaux présentés dans cette thèse s'inscrivent suivant deux approches majeures : une approche par la modélisation avec la simulation de l'extraction de la disparité rétinienne au niveau cortical et une approche expérimentale avec l'étude de l'influence de la disparité rétinienne sur l'attention visuelle pendant l'exploration de scènes visuelles stéréoscopiques avec enregistrements oculométriques. Le modèle proposé est construit en utilisant les données physiologiques du cortex visuel primaire V1 disponibles dans la littérature. Il effectue une estimation de la disparité rétinienne à partir des réponses modélisées des cellules simples et complexes de V1. Nous adoptons une approche bio-inspirée à deux niveaux. Le premier concerne l'architecture globale d'organisation et d'interaction des cellules corticales réalisant l'extraction d'informations à différentes fréquences spatiales, orientations et disparités, pour obtenir une estimation locale de la disparité rétinienne. Le second niveau concerne la configuration des cellules corticales implémentées comme des opérateurs de filtrage spatial. La partie expérimentale se divise elle-même en deux parties. En effet, l'utilisation de données oculométriques d'exploration de scènes 3D nécessite une étape préalable de calibration. Ainsi, nous développons une méthode de calibration 3D permettant de suivre la profondeur du regard à partir des coordonnées binoculaires enregistrées par oculométrie. Ensuite, nous analysons l'influence de la disparité rétinienne sur l'exploration visuelle de différentes catégories de scènes naturelles basées sur la présence d'indices de profondeur monoculaires et binoculaires. Nous étudions l'influence de la dominance oculaire, du biais de centralité et du biais de profondeur sur l'exploration pour chaque catégorie d'image. Un modèle de saillance 2D se montre inadapté pour prédire les zones saillantes en 3D mais également en 2D. L'information de profondeur doit être intégrée dans le calcul de la saillance grâce à la disparité rétinienne et grâce aux autres indices de profondeur pour expliquer pleinement l'exploration 2D et 3D

From binocular retina to the first stages of the visual cortex for the 3D visual perception : model and oculometric experiments

La vision de la profondeur ou communément appelée « vision 3D » permet d'interpréter les relations spatiales tridimensionnelles entre les objets de la scène visuelle et confère à l'homme une grande précision dans ses interactions avec l'environnement. La vision 3D repose sur de nombreux mécanismes d'analyse du signal visuel dont la plupart gardent tout leur pouvoir informationnel lors de la stimulation d'un seul œil (indices monoculaires) mais dont certains nécessitent la stimulation des deux yeux (indices binoculaires). Cette thèse se concentre sur les mécanismes nécessitant les deux yeux qui mettent en jeu la différence de point de vue entre les deux yeux, aussi appelée disparité rétinienne. Les travaux présentés dans cette thèse s'inscrivent suivant deux approches majeures : une approche par la modélisation avec la simulation de l'extraction de la disparité rétinienne au niveau cortical et une approche expérimentale avec l'étude de l'influence de la disparité rétinienne sur l'attention visuelle pendant l'exploration de scènes visuelles stéréoscopiques avec enregistrements oculométriques. Le modèle proposé est construit en utilisant les données physiologiques du cortex visuel primaire V1 disponibles dans la littérature. Il effectue une estimation de la disparité rétinienne à partir des réponses modélisées des cellules simples et complexes de V1. Nous adoptons une approche bio-inspirée à deux niveaux. Le premier concerne l'architecture globale d'organisation et d'interaction des cellules corticales réalisant l'extraction d'informations à différentes fréquences spatiales, orientations et disparités, pour obtenir une estimation locale de la disparité rétinienne. Le second niveau concerne la configuration des cellules corticales implémentées comme des opérateurs de filtrage spatial. La partie expérimentale se divise elle-même en deux parties. En effet, l'utilisation de données oculométriques d'exploration de scènes 3D nécessite une étape préalable de calibration. Ainsi, nous développons une méthode de calibration 3D permettant de suivre la profondeur du regard à partir des coordonnées binoculaires enregistrées par oculométrie. Ensuite, nous analysons l'influence de la disparité rétinienne sur l'exploration visuelle de différentes catégories de scènes naturelles basées sur la présence d'indices de profondeur monoculaires et binoculaires. Nous étudions l'influence de la dominance oculaire, du biais de centralité et du biais de profondeur sur l'exploration pour chaque catégorie d'image. Un modèle de saillance 2D se montre inadapté pour prédire les zones saillantes en 3D mais également en 2D. L'information de profondeur doit être intégrée dans le calcul de la saillance grâce à la disparité rétinienne et grâce aux autres indices de profondeur pour expliquer pleinement l'exploration 2D et 3D.Depth vision or « 3D vision » can interpret tridimensional spatial relations between objects in a visual scene and gives humans a good precision of interaction with their environment. 3D vision uses several kinds of mechanisms to analyze visual signal. Some keep their power during a monocular stimulation (monocular depth cues) but others need a binocular stimulation (binocular depth cues). This thesis focuses on the binocular mechanism which uses the difference of point of view between the two eyes (also called retinal disparity). The work presented in this thesis follows two main approaches: the modeling of the retinal disparity extraction at the cortical level, and an experiment to analyze the influence of retinal disparity on visual attention during the exploration of natural stereoscopic scenes with eye tracking recording. The proposed model is built from physiologic data of primary visual cortex V1 found in the literature. Our model makes an estimation of the retinal disparity from modeled responses of simple and complex cells of V1. We take a bio-inspired approach at two levels. The first level concerns the global architecture of the organization and the interaction of cortical cells which extract the information at different spatial frequencies, orientations and disparities. The second level concerns the configuration of cortical cells implemented like spatial filters. The experimental part is subdivided into two parts. Indeed, the use of eye-tracking data of 3D scenes exploration needs a calibration step. Hence, we developed a 3D calibration method allowing us to track the depth of the gaze from the recorded binocular coordinates. Then, we analyze the influence of retinal disparity in the visual exploration of different categories of natural scenes based on the presence of monocular and binocular depth cues. The ocular dominance, the central bias and the depth bias are also studied in this paradigm. We show that a 2D saliency model is not adapted to predict the salient zone during 3D viewing but also during 2D viewing. The depth information must be integrated in saliency computation thanks to retinal disparity and monocular depth cues to explain fully the visual exploration both in 2D and 3D

Assessment of Tissue Injury in Severe Brain Trauma

International audienceWe report our methodological developments to investigate, in a multi-center study using mean diffusivity, the tissue damage caused by a severe traumatic brain injury (GSC<9) in the 10 days post-event. To assess the diffuse aspect of the injury, we fuse several atlases to parcel cortical, subcortical and WM structures into well identified regions where MD values are computed and compared to normative values. We used P-LOCUS to provide brain tissue segmentation and exclude voxels labeled as CSF, ventricles and hemorrhagic lesion and then automatically detect the lesion load. Preliminary results demonstrate that our method is coherent with expert opinion in the identification of lesions. We outline the challenges posed in automatic analysis for TBI

Traumatic Brain Lesion Quantification based on Mean Diffusivity Changes

International audienceWe report the evaluation of an automated method for quantification of brain tissue damage, caused by a severe traumatic brain injury, using mean diffusivity computed from MR diffusion images. Our automatic results obtained on realistic phantoms and real patient images 10 days post-event provided by nine different centers were coherent with four expert manually identified lesions. For realistic phantoms automated method scores were equal to 0.77, 0.77 and 0.83 for Dice, Precision and Sensibility respectively compared to 0.78, 0.72 and 0.86 for the experts. The inter correlation class (ICC) was 0.79. For 7/9 real cases 0.57, 0.50 and 0.70 were respectively obtained for automated method compared to 0.60, 0.52 and 0.78 for experts with ICC=0.71. Additionally, we detail the quality control module used to pool data from various image provider centers. This study clearly demonstrates the validity of the proposed automated method to eventually compute in a multi-centre project, the lesional load following brain trauma based on MD changes

Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images

International audienceObjectives Determining the volume of brain lesions after trauma is challenging. Manual delineation is observer-dependent and time-consuming and cannot therefore be used in routine practice. The study aimed to evaluate the feasibility of an automated atlas-based quantification procedure (AQP) based on the detection of abnormal mean diffusivity (MD) values computed from diffusion-weighted MR images. Methods The performance of AQP was measured against manual delineation consensus by independent raters in two series of experiments based on: (i) realistic trauma phantoms ( n = 5) where low and high MD values were assigned to healthy brain images according to the intensity, form and location of lesion observed in real TBI cases; (ii) severe TBI patients ( n = 12 patients) who underwent MR imaging within 10 days after injury. Results In realistic TBI phantoms, no statistical differences in Dice similarity coefficient, precision and brain lesion volumes were found between AQP, the rater consensus and the ground truth lesion delineations. Similar findings were obtained when comparing AQP and manual annotations for TBI patients. The intra-class correlation coefficient between AQP and manual delineation was 0.70 in realistic phantoms and 0.92 in TBI patients. The volume of brain lesions detected in TBI patients was 59 ml (19–84 ml) (median; 25–75th centiles). Conclusions Our results support the feasibility of using an automated quantification procedure to determine, with similar accuracy to manual delineation, the volume of low and high MD brain lesions after trauma, and thus allow the determination of the type and volume of edematous brain lesions. This approach had comparable performance with manual delineation by a panel of experts. It will be tested in a large cohort of patients enrolled in the multicenter OxyTC trial (NCT02754063)