Automated segmentation of multiple red blood cells with digital holographic microscopy.

We present a method to automatically segment red blood cells (RBCs) visualized by digital holographic microscopy (DHM), which is based on the marker-controlled watershed algorithm. Quantitative phase images of RBCs can be obtained by using off-axis DHM along to provide some important information about each RBC, including size, shape, volume, hemoglobin content, etc. The most important process of segmentation based on marker-controlled watershed is to perform an accurate localization of internal and external markers. Here, we first obtain the binary image via Otsu algorithm. Then, we apply morphological operations to the binary image to get the internal markers. We then apply the distance transform algorithm combined with the watershed algorithm to generate external markers based on internal markers. Finally, combining the internal and external markers, we modify the original gradient image and apply the watershed algorithm. By appropriately identifying the internal and external markers, the problems of oversegmentation and undersegmentation are avoided. Furthermore, the internal and external parts of the RBCs phase image can also be segmented by using the marker-controlled watershed combined with our method, which can identify the internal and external markers appropriately. Our experimental results show that the proposed method achieves good performance in terms of segmenting RBCs and could thus be helpful when combined with an automated classification of RBCs.

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.

Visual representation of food in the brain : effects of repeated exposure and gut hormone secretion

The thesis at hand is concerned with the spatio-temporal brain mechanisms of visual food perception as investigated by electrical neuroimaging. Due to the increasing prevalence of obesity and its associated challenges for public health care, there is a need to better understand behavioral and brain processes underlying food perception and food-based decision-making. The first study (Study A) of this thesis was concerned with the role of repeated exposure to visual food cues. In our everyday lives we constantly and repeatedly encounter food and these exposures influence our food choices and preferences. In Study A, we therefore applied electrical neuroimaging analyses of visual evoked potentials to investigate the spatio-temporal brain dynamics linked to the repeated viewing of high- and low-energy food cues (published manuscript: "The role of energetic value in dynamic brain response adaptation during repeated food image viewing" (Lietti et al., 2012)). In this study, we found that repetitions differentially affect behavioral and brain mechanisms when high-energy, as opposed to low-energy foods and non-food control objects, were viewed. The representation of high-energy food remained invariant between initial and repeated exposures indicating that the sight of high-energy dense food induces less behavioral and neural adaptation than the sight of low-energy food and non-food control objects. We discuss this finding in the context of the higher salience (due to greater motivation and higher reward or hedonic valuation) of energy- dense food that likely generates a more mnemonically stable representation. In turn, this more invariant representation of energy-dense food is supposed to (partially) explain why these foods are over-consumed despite of detrimental health consequences. In Study Β we investigated food responsiveness in patients who had undergone Roux-en-Y gastric bypass surgery to overcome excessive obesity. This type of gastric bypass surgery is not only known to alter food appreciation, but also the secretion patterns of adipokines and gut peptides. Study Β aimed at a comprehensive and interdisciplinary investigation of differences along the gut-brain axis in bypass-operated patients as opposed to weight-matched non-operated controls. On the one hand, the spatio-temporal brain dynamics to the visual perception of high- vs. low-energy foods under differing states of motivation towards food intake (i.e. pre- and post-prandial) were assessed and compared between groups. On the other hand, peripheral gut hormone measures were taken in pre- and post-prandial nutrition state and compared between groups. In order to evaluate alterations in the responsiveness along the gut-brain-axis related to gastric bypass surgery, correlations between both measures were compared between both participant groups. The results revealed that Roux-en- Y gastric bypass surgery alters the spatio-temporal brain dynamics to the perception of high- and low-energy food cues, as well as the responsiveness along the gut-brain-axis. The potential role of these response alterations is discussed in relation to previously observed changes in physiological factors and food intake behavior post-Roux-en-Y gastric bypass surgery. By doing so, we highlight potential behavioral, neural and endocrine (i.e. gut hormone) targets for the future development of intervention strategies for deviant eating behavior and obesity. Together, the studies showed that the visual representation of foods in the brain is plastic and that modulations in neural activity are already noted at early stages of visual processing. Different factors of influence such as a repeated exposure, Roux-en-Y gastric bypass surgery, motivation (nutrition state), as well as the energy density of the visually perceived food were identified. En raison de la prévalence croissante de l'obésité et du défi que cela représente en matière de santé publique, une meilleure compréhension des processus comportementaux et cérébraux liés à la nourriture sont nécessaires. En particulier, cette thèse se concentre sur l'investigation des mécanismes cérébraux spatio-temporels liés à la perception visuelle de la nourriture. Nous sommes quotidiennement et répétitivement exposés à des images de nourriture. Ces expositions répétées influencent nos choix, ainsi que nos préférences alimentaires. La première étude (Study A) de cette thèse investigue donc l'impact de ces exposition répétée à des stimuli visuels de nourriture. En particulier, nous avons comparé la dynamique spatio-temporelle de l'activité cérébrale induite par une exposition répétée à des images de nourriture de haute densité et de basse densité énergétique. (Manuscrit publié: "The role of energetic value in dynamic brain response adaptation during repeated food image viewing" (Lietti et al., 2012)). Dans cette étude, nous avons pu constater qu'une exposition répétée à des images représentant de la nourriture de haute densité énergétique, par opposition à de la nourriture de basse densité énergétique, affecte les mécanismes comportementaux et cérébraux de manière différente. En particulier, la représentation neurale des images de nourriture de haute densité énergétique est similaire lors de l'exposition initiale que lors de l'exposition répétée. Ceci indique que la perception d'images de nourriture de haute densité énergétique induit des adaptations comportementales et neurales de moindre ampleur par rapport à la perception d'images de nourriture de basse densité énergétique ou à la perception d'une « catégorie contrôle » d'objets qui ne sont pas de la nourriture. Notre discussion est orientée sur les notions prépondérantes de récompense et de motivation qui sont associées à la nourriture de haute densité énergétique. Nous suggérons que la nourriture de haute densité énergétique génère une représentation mémorielle plus stable et que ce mécanisme pourrait (partiellement) être sous-jacent au fait que la nourriture de haute densité énergétique soit préférentiellement consommée. Dans la deuxième étude (Study Β) menée au cours de cette thèse, nous nous sommes intéressés aux mécanismes de perception de la nourriture chez des patients ayant subi un bypass gastrique Roux- en-Y, afin de réussir à perdre du poids et améliorer leur santé. Ce type de chirurgie est connu pour altérer la perception de la nourriture et le comportement alimentaire, mais également la sécrétion d'adipokines et de peptides gastriques. Dans une approche interdisciplinaire et globale, cette deuxième étude investigue donc les différences entre les patients opérés et des individus « contrôles » de poids similaire au niveau des interactions entre leur activité cérébrale et les mesures de leurs hormones gastriques. D'un côté, nous avons investigué la dynamique spatio-temporelle cérébrale de la perception visuelle de nourriture de haute et de basse densité énergétique dans deux états physiologiques différent (pre- et post-prandial). Et de l'autre, nous avons également investigué les mesures physiologiques des hormones gastriques. Ensuite, afin d'évaluer les altérations liées à l'intervention chirurgicale au niveau des interactions entre la réponse cérébrale et la sécrétion d'hormone, des corrélations entre ces deux mesures ont été comparées entre les deux groupes. Les résultats révèlent que l'intervention chirurgicale du bypass gastrique Roux-en-Y altère la dynamique spatio-temporelle de la perception visuelle de la nourriture de haute et de basse densité énergétique, ainsi que les interactions entre cette dernière et les mesures périphériques des hormones gastriques. Nous discutons le rôle potentiel de ces altérations en relation avec les modulations des facteurs physiologiques et les changements du comportement alimentaire préalablement déjà démontrés. De cette manière, nous identifions des cibles potentielles pour le développement de stratégies d'intervention future, au niveau comportemental, cérébral et endocrinien (hormones gastriques) en ce qui concerne les déviances du comportement alimentaire, dont l'obésité. Nos deux études réunies démontrent que la représentation visuelle de la nourriture dans le cerveau est plastique et que des modulations de l'activité neurale apparaissent déjà à un stade très précoce des mécanismes de perception visuelle. Différents facteurs d'influence comme une exposition repetee, le bypass gastrique Roux-en-Y, la motivation (état nutritionnel), ainsi que la densité énergétique de la nourriture qui est perçue ont pu être identifiés.

Space for thought: Representation of body boundaries and intellectual efficiency in children

Aim: The psychoanalytic theories of Bion, Anzieu, Berger and Gibello postulate that the development of thinking depends upon the formation of a psychic space. This thinking space has its origin in the body and in our interpersonal relations. This study aims to validate this psychodynamic hypothesis. Method: A group of 8- to 14-year-old children participated in this research. The presence of a thinking space was operationalized by the "barrier" and "penetration" scores on the Rorschach's Fisher and Cleveland scales and intellectual efficiency was measured using a short version of the WISC-IV. Results: Results show that extreme scores on the "barrier" and "penetration" variables predict a lower intellectual level than average scores on the same variables. Conclusion: The development of thinking and personality are undoubtedly linked and the "barrier" and "penetration" variables are useful measures when evaluating the development of a space for thought.

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

Monitoring of illicit pill distribution networks using an image collection exploration framework

This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.

Semi-supervised remote sensing image classification with cluster kernels

A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.

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.

Representation of motor habit in a sequence of repetitive reach and grasp movements performed by macaque monkeys: evidence for a contribution of the dorsolateral prefrontal cortex.

In the context of an autologous cell transplantation study, a unilateral biopsy of cortical tissue was surgically performed from the right dorsolateral prefrontal cortex (dlPFC) in two intact adult macaque monkeys (dlPFC lesioned group), together with the implantation of a chronic chamber providing access to the left motor cortex. Three other monkeys were subjected to the same chronic chamber implantation, but without dlPFC biopsy (control group). All monkeys were initially trained to perform sequential manual dexterity tasks, requiring precision grip. The motor performance and the prehension's sequence (temporal order to grasp pellets from different spatial locations) were analysed for each hand. Following the surgery, transient and moderate deficits of manual dexterity per se occurred in both groups, indicating that they were not due to the dlPFC lesion (most likely related to the recording chamber implantation and/or general anaesthesia/medication). In contrast, changes of motor habit were observed for the sequential order of grasping in the two monkeys with dlPFC lesion only. The changes were more prominent in the monkey subjected to the largest lesion, supporting the notion of a specific effect of the dlPFC lesion on the motor habit of the monkeys. These observations are reminiscent of previous studies using conditional tasks with delay that have proposed a specialization of the dlPFC for visuo-spatial working memory, except that this is in a different context of "free-will", non-conditional manual dexterity task, without a component of working memory.

Hemispheric competence for auditory spatial representation.

Sound localization relies on the analysis of interaural time and intensity differences, as well as attenuation patterns by the outer ear. We investigated the relative contributions of interaural time and intensity difference cues to sound localization by testing 60 healthy subjects: 25 with focal left and 25 with focal right hemispheric brain damage. Group and single-case behavioural analyses, as well as anatomo-clinical correlations, confirmed that deficits were more frequent and much more severe after right than left hemispheric lesions and for the processing of interaural time than intensity difference cues. For spatial processing based on interaural time difference cues, different error types were evident in the individual data. Deficits in discriminating between neighbouring positions occurred in both hemispaces after focal right hemispheric brain damage, but were restricted to the contralesional hemispace after focal left hemispheric brain damage. Alloacusis (perceptual shifts across the midline) occurred only after focal right hemispheric brain damage and was associated with minor or severe deficits in position discrimination. During spatial processing based on interaural intensity cues, deficits were less severe in the right hemispheric brain damage than left hemispheric brain damage group and no alloacusis occurred. These results, matched to anatomical data, suggest the existence of a binaural sound localization system predominantly based on interaural time difference cues and primarily supported by the right hemisphere. More generally, our data suggest that two distinct mechanisms contribute to: (i) the precise computation of spatial coordinates allowing spatial comparison within the contralateral hemispace for the left hemisphere and the whole space for the right hemisphere; and (ii) the building up of global auditory spatial representations in right temporo-parietal cortices.

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.