Perceção visual na avaliação diagnóstica em mamografia: uma revisão sistemática

Introdução – Na avaliação diagnóstica em mamografia, o desempenho do radiologista pode estar sujeito a erros de diagnóstico. Objetivo – Descrever a importância da perceção visual na análise da mamografia, identificando os principais fatores que contribuem para a perceção visual do radiologista e que condicionam a acuidade diagnóstica. Metodologia – Estudo descritivo baseado numa revisão sistemática de literatura através da PubMed e da Science Direct. Foram incluídos 42 artigos que respeitavam, pelo menos, um dos critérios de inclusão no estudo. Para a seleção das referências foi utilizada a metodologia PRISMA, constituída por 4 fases: identificação, seleção preliminar, elegibilidade e estudos incluídos. Resultados – Na avaliação diagnóstica em mamografia, a perceção visual está intimamente relacionada com: 1) diferentes parâmetros visuais e da motilidade ocular (acuidade visual, sensibilidade ao contraste e à luminância e movimentos oculares); 2) com condições de visualização de uma imagem (iluminância da sala e luminância do monitor); e 3) fadiga ocular provocada pela observação diária consecutiva de imagens. Conclusões – A perceção visual pode ser influenciada por 3 categorias de erros observados: erros de pesquisa (lesões não são fixadas pela fóvea), erros de reconhecimento (lesões fixadas, mas não durante o tempo suficiente) e erros de decisão (lesões fixadas, mas não identificadas como suspeitas). Os estudos analisados sobre perceção visual, atenção visual e estratégia visual, bem como os estudos sobre condições de visualização não caracterizam a função visual dos observadores. Para uma avaliação correta da perceção visual em mamografia deverão ser efetuados estudos que correlacionem a função visual com a qualidade diagnóstica. ABSTRACT - Introduction – Diagnostic evaluation in mammography could be influenced by the radiologist performance that could be under diagnostic errors. Aims – To describe the importance of radiologist visual perception in mammographic diagnostic evaluation and to identify the main factors that contribute to diagnostic accuracy. Methods – In this systematic review 42 references were included based on inclusion criteria (PubMed and Science Direct). PRISMA method was used to select the references following 4 steps: identification, screening, eligibility and included references. Results – Visual perception in mammography diagnostic evaluation is related with: 1) visual parameters and ocular motility (visual acuity, contrast sensitivity and luminance and ocular movements); 2) image visualization environment (room iluminance and monitor luminance); and 3) eyestrain caused by image daily consecutive observation. Conclusions – Visual perception can be influenced by three errors categories: search errors (lesions are never looked at with high-resolution foveal vision), recognition errors (lesions are looked at, but not long enough to detect or recognize) and decision errors (lesions are looked at for long periods of time but are still missed). The reviewed studies concerning visual perception, visual attention, visual strategies and image visualization environment do not describe observer’s visual function. An accurate evaluation of visual perception in mammography must include visual function analysis.

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

An Interface to Retrieve Personal Memories Using an Iconic Visual Language

Relevant past events can be remembered when visualizing related pictures. The main difficulty is how to find these photos in a large personal collection. Query definition and image annotation are key issues to overcome this problem. The former is relevant due to the diversity of the clues provided by our memory when recovering a past moment and the later because images need to be annotated with information regarding those clues to be retrieved. Consequently, tools to recover past memories should deal carefully with these two tasks. This paper describes a user interface designed to explore pictures from personal memories. Users can query the media collection in several ways and for this reason an iconic visual language to define queries is proposed. Automatic and semi-automatic annotation is also performed using the image content and the audio information obtained when users show their images to others. The paper also presents the user interface evaluation based on tests with 58 participants.

10 kVp rule – An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose - This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose (E) for pelvis using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Methods and materials - To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60–120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the two alternative forced choice (2AFC) visual grading software. PCXMC software was used to estimate E. Results - A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p > 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. E results show a statistically significant decrease (p = 0.000) on the 75th quartile from 0.37 mSv at 60 kVp to 0.13 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion - Using the 10 kVp rule, no significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant E reduction is observed.

Sistema visual para Ground Truth de sistemas autónomos

Este trabalho visa contribuir para o desenvolvimento de um sistema de visão multi-câmara para determinação da localização, atitude e seguimento de múltiplos objectos, para ser utilizado na unidade de robótica do INESCTEC, e resulta da necessidade de ter informação externa exacta que sirva de referência no estudo, caracterização e desenvolvimento de algoritmos de localização, navegação e controlo de vários sistemas autónomos. Com base na caracterização dos veículos autónomos existentes na unidade de robótica do INESCTEC e na análise dos seus cenários de operação, foi efectuado o levantamento de requisitos para o sistema a desenvolver. Foram estudados os fundamentos teóricos, necessários ao desenvolvimento do sistema, em temas relacionados com visão computacional, métodos de estimação e associação de dados para problemas de seguimento de múltiplos objectos . Foi proposta uma arquitectura para o sistema global que endereça os vários requisitos identi cados, permitindo a utilização de múltiplas câmaras e suportando o seguimento de múltiplos objectos, com ou sem marcadores. Foram implementados e validados componentes da arquitectura proposta e integrados num sistema para validação, focando na localização e seguimento de múltiplos objectos com marcadores luminosos à base de Light-Emitting Diodes (LEDs). Nomeadamente, os módulos para a identi cação dos pontos de interesse na imagem, técnicas para agrupar os vários pontos de interesse de cada objecto e efectuar a correspondência das medidas obtidas pelas várias câmaras, método para a determinação da posição e atitude dos objectos, ltro para seguimento de múltiplos objectos. Foram realizados testes para validação e a nação do sistema implementado que demonstram que a solução encontrada vai de encontro aos requisitos, e foram identi cadas as linhas de trabalho para a continuação do desenvolvimento do sistema global.

10 kVp rule - An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose: This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose for pelvis using automatic exposure control (AEC) and non-AEC in a computed radiography (CR) system. Methods and Materials: To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60-120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the 2 AFC visual grading software. PCXMC software was used to estimate the effective dose. Results: A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p> 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. Effective dose results show a statistical significant decrease (p=0.000) on the 75th quartile from 0.3 mSv at 60 kVp to 0.1 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion: No significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant effective dose reduction is observed.

PINPIN a-Si: H based structures for X-ray image detection using the laser scanning technique

Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Vision-Based Assisted Teleoperation for Inspection Tasks with a Small ROV

It is well-known that ROVs require human intervention to guarantee the success of their assignment, as well as the equipment safety. However, as its teleoperation is quite complex to perform, there is a need for assisted teleoperation. This study aims to take on this challenge by developing vision-based assisted teleoperation maneuvers, since a standard camera is present in any ROV. The proposed approach is a visual servoing solution, that allows the user to select between several standard image processing methods and is applied to a 3-DOF ROV. The most interesting characteristic of the presented system is the exclusive use of the camera data to improve the teleoperation of an underactuated ROV. It is demonstrated through the comparison and evaluation of standard implementations of different vision methods and the execution of simple maneuvers to acquire experimental results, that the teleoperation of a small ROV can be drastically improved without the need to install additional sensors.

Calibration Method for Underwater Visual Ground-Truth System

This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Minimal computation structures for visual information applications based on printed electronics

In the early nineties, Mark Weiser wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. According to Weiser, computers require too much attention from the user, drawing his focus from the tasks at hand. Instead of being the centre of attention, computers should be so natural that they would vanish into the human environment. Computers become not only truly pervasive but also effectively invisible and unobtrusive to the user. This requires not only for smaller, cheaper and low power consumption computers, but also for equally convenient display solutions that can be harmoniously integrated into our surroundings. With the advent of Printed Electronics, new ways to link the physical and the digital worlds became available. By combining common printing techniques such as inkjet printing with electro-optical functional inks, it is starting to be possible not only to mass-produce extremely thin, flexible and cost effective electronic circuits but also to introduce electronic functionalities into products where it was previously unavailable. Indeed, Printed Electronics is enabling the creation of novel sensing and display elements for interactive devices, free of form factor. At the same time, the rise in the availability and affordability of digital fabrication technologies, namely of 3D printers, to the average consumer is fostering a new industrial (digital) revolution and the democratisation of innovation. Nowadays, end-users are already able to custom design and manufacture on demand their own physical products, according to their own needs. In the future, they will be able to fabricate interactive digital devices with user-specific form and functionality from the comfort of their homes. This thesis explores how task-specific, low computation, interactive devices capable of presenting dynamic visual information can be created using Printed Electronics technologies, whilst following an approach based on the ideals behind Personal Fabrication. Focus is given on the use of printed electrochromic displays as a medium for delivering dynamic digital information. According to the architecture of the displays, several approaches are highlighted and categorised. Furthermore, a pictorial computation model based on extended cellular automata principles is used to programme dynamic simulation models into matrix-based electrochromic displays. Envisaged applications include the modelling of physical, chemical, biological, and environmental phenomena.

Vision-based representation and recognition of human activities in image sequences

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013

Development of CBCT-based prostate setup correction strategies and impact of rectal distension.

BACKGROUND: Cone-beam computed tomography (CBCT) image-guided radiotherapy (IGRT) systems are widely used tools to verify and correct the target position before each fraction, allowing to maximize treatment accuracy and precision. In this study, we evaluate automatic three-dimensional intensity-based rigid registration (RR) methods for prostate setup correction using CBCT scans and study the impact of rectal distension on registration quality. METHODS: We retrospectively analyzed 115 CBCT scans of 10 prostate patients. CT-to-CBCT registration was performed using (a) global RR, (b) bony RR, or (c) bony RR refined by a local prostate RR using the CT clinical target volume (CTV) expanded with 1-to-20-mm varying margins. After propagation of the manual CT contours, automatic CBCT contours were generated. For evaluation, a radiation oncologist manually delineated the CTV on the CBCT scans. The propagated and manual CBCT contours were compared using the Dice similarity and a measure based on the bidirectional local distance (BLD). We also conducted a blind visual assessment of the quality of the propagated segmentations. Moreover, we automatically quantified rectal distension between the CT and CBCT scans without using the manual CBCT contours and we investigated its correlation with the registration failures. To improve the registration quality, the air in the rectum was replaced with soft tissue using a filter. The results with and without filtering were compared. RESULTS: The statistical analysis of the Dice coefficients and the BLD values resulted in highly significant differences (p<10(-6)) for the 5-mm and 8-mm local RRs vs the global, bony and 1-mm local RRs. The 8-mm local RR provided the best compromise between accuracy and robustness (Dice median of 0.814 and 97% of success with filtering the air in the rectum). We observed that all failures were due to high rectal distension. Moreover, the visual assessment confirmed the superiority of the 8-mm local RR over the bony RR. CONCLUSION: The most successful CT-to-CBCT RR method proved to be the 8-mm local RR. We have shown the correlation between its registration failures and rectal distension. Furthermore, we have provided a simple (easily applicable in routine) and automatic method to quantify rectal distension and to predict registration failure using only the manual CT contours.

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.

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.