56 research outputs found

    Longitudinal prediction of infant MR images with multi-contrast perceptual adversarial learning

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    The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimaging studies of early brain development. However, missing data at different time points is an unavoidable occurrence in longitudinal studies owing to participant attrition and scan failure. Compared to dropping incomplete data, data imputation is considered a better solution to address such missing data in order to preserve all available samples. In this paper, we adapt generative adversarial networks (GAN) to a new application: longitudinal image prediction of structural MRI in the first year of life. In contrast to existing medical image-to-image translation applications of GANs, where inputs and outputs share a very close anatomical structure, our task is more challenging as brain size, shape and tissue contrast vary significantly between the input data and the predicted data. Several improvements over existing GAN approaches are proposed to address these challenges in our task. To enhance the realism, crispness, and accuracy of the predicted images, we incorporate both a traditional voxel-wise reconstruction loss as well as a perceptual loss term into the adversarial learning scheme. As the differing contrast changes in T1w and T2w MR images in the first year of life, we incorporate multi-contrast images leading to our proposed 3D multi-contrast perceptual adversarial network (MPGAN). Extensive evaluations are performed to assess the qualityand fidelity of the predicted images, including qualitative and quantitative assessments of the image appearance, as well as quantitative assessment on two segmentation tasks. Our experimental results show that our MPGAN is an effective solution for longitudinal MR image data imputation in the infant brain. We further apply our predicted/imputed images to two practical tasks, a regression task and a classification task, in order to highlight the enhanced task-related performance following image imputation. The results show that the model performance in both tasks is improved by including the additional imputed data, demonstrating the usability of the predicted images generated from our approach

    A Survey on Deep Learning in Medical Image Registration: New Technologies, Uncertainty, Evaluation Metrics, and Beyond

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    Over the past decade, deep learning technologies have greatly advanced the field of medical image registration. The initial developments, such as ResNet-based and U-Net-based networks, laid the groundwork for deep learning-driven image registration. Subsequent progress has been made in various aspects of deep learning-based registration, including similarity measures, deformation regularizations, and uncertainty estimation. These advancements have not only enriched the field of deformable image registration but have also facilitated its application in a wide range of tasks, including atlas construction, multi-atlas segmentation, motion estimation, and 2D-3D registration. In this paper, we present a comprehensive overview of the most recent advancements in deep learning-based image registration. We begin with a concise introduction to the core concepts of deep learning-based image registration. Then, we delve into innovative network architectures, loss functions specific to registration, and methods for estimating registration uncertainty. Additionally, this paper explores appropriate evaluation metrics for assessing the performance of deep learning models in registration tasks. Finally, we highlight the practical applications of these novel techniques in medical imaging and discuss the future prospects of deep learning-based image registration

    Volumetria de estruturas cerebrais profundas com imagem RM

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    A Ressonância Magnética é uma técnica de diagnóstico por imagem frequentemente presente na prática clínica e em constante desenvolvimento. É um método moderno e sofisticado de aquisição de imagem e sinal, com elevada qualidade de imagem, relevante para a volumetria cerebral. A volumetria associada a RM facilita a comparação de dados volumétricos por possibilitar a obtenção de dados mais concretos a nível dos volumes das estruturas cerebrais. Atualmente, o interesse no desenvolvimento de metodologias para a análise de estruturas e medição volumétrica tem vindo a aumentar, sendo que, é desejável que seja um método mais automático, rápido e eficaz e que realize a segmentação de imagem com pouca intervenção do operador. Este estudo experimental tem como objetivo a comparação do volume das estruturas subcorticais entre 2 softwares diferentes a fim de testar a robustez de ambos. Os softwares utilizados, o FreeSurfer e o VolBrain, implementam estratégias de segmentação (semi-)automáticas, seguindo paradigmas algorítmicos diferentes. Ambos os softwares são de distribuição livre e utilizados para estudos de anatomia cerebral, incluindo a segmentação de anatomia cortical e subcortical, fornecendo os respetivos volumes. Inicialmente fez-se um estudo sobre os conceitos de aquisição de imagem cerebral por RM e sobre as estratégias de segmentação deformáveis existentes. A segmentação por modelos deformáveis revelou-se produtiva com resultados prometedores, devido ao facto de ser um método flexível e capaz de segmentar casos mais complexos. Antes de realizar a segmentação da nossa base de dados, efetuou-se IV uma análise sobre os softwares utilizados, as estratégias de segmentação e as propriedades de ambos, onde foi possível observar o modus operandi de cada um, assim como as diferenças entre estes. De seguida realizou-se o processamento das imagens da amostra, composta por 35 casos com diferentes estados de saúde (saudável, presença de tumor ou quisto, epilepsia, autismo), de ambos os sexos e com idades entre os 5 e os 50 anos. No fim da segmentação, ambos forneceram dados volumétricos das estruturas subcorticais, que foram devidamente tabelados a fim de serem analisados e comparados. Para uma melhor visualização comparativa da diferença dos volumes obtidos realizou-se uma rede no MeVisLab que permitiu a sobreposição de ambos os resultados. Os resultados demonstram que o FreeSurfer fornece valores, no geral, significativamente superiores aos do VolBrain, em alguns casos mais relevantes que outros. Tais diferenças são possíveis devido a questões algorítmicas e de pipeline. O VolBrain foi considerado mais fiável a nível de resultados que o FreeSurfer, pois este último tem tendência a superestimar as estruturas subcorticais.Magnetic resonance imaging (MRI) is a diagnostic imaging technique frequently present in the clinical practice and in constant development. It is a modern and sophisticated method of image and signal acquisition, with high image quality, relevant to cerebral volumetry. Volumetry associated with MRI facilitates the comparison of volumetric data allowing to obtain more solid data on the volumes of cerebral structures. Currently, the interest in the development of methodologies for the analyses of structures and volumetric measurement has been increasing, so it is desirable that it becomes a more automated, fast and efficient method and able to perform image segmentation with reduced operator intervention. This experimental study aims to compare the volume of subcortical structures between two different softwares to test the robustness of both. The softwares used, FreeSurfer and VolBrain, implements (semi) automatic segmentation strategies, following different algorithmic paradigms. Both softwares are freely available and are used for cerebral anatomy studies, including the segmentation of cortical and subcortical anatomy, providing the respective volumes. Initially, a study was made focusing on the concepts of MR imaging and on the existing deformable segmentation strategies. The segmentation by deformable models proved to be productive with promising results, due to the fact that it is a flexible method capable of segmenting more complex cases. Before segmenting our data, we analyzed the characteristics of the softwares used, the segmentation strategies and the properties of both, being possible to observe the modus operandi of each one, as well as the differences between them. Next, the images of the sample, composed of VI 35 cases with different health states (healthy, presence of tumor or cyst, epilepsy, autism), of both genders and aged between 5 and 50 years, were processed. At the end of segmentation, both provided volumetric data from subcortical structures, which were tabulated for analysis and comparisons. For a better comparative visualization of the difference of the obtained volumes, a network in MeVisLab was performed to inspect the overlap of both results. The results showed that FreeSurfer provides values that are generally significantly higher than those of VolBrain, in some cases more relevant than others. Such differences are possible due to algorithmic and pipeline issues. VolBrain was considered more reliable in terms of results than FreeSurfer, since the latter tends to overestimate the subcortical structures.Mestrado em Tecnologias da Imagem Médic

    Common minds, uncommon thoughts: a philosophical anthropological investigation of uniquely human creative behavior, with an emphasis on artistic ability, religious reflection, and scientific study

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    The aim of this dissertation is to create a naturalistic philosophical picture of creative capacities that are specific to our species, focusing on artistic ability, religious reflection, and scientific study. By integrating data from diverse domains (evolutionary and developmental psychology, cognitive anthropology and archeology, neuroscience) within a philosophical anthropological framework, I have presented a cognitive and evolutionary approach to the question of why humans, but not other animals engage in such activities. Through an application of cognitive and evolutionary perspectives to the study of these behaviors, I have sought to provide a more solid footing for philosophical anthropological discussions of uniquely human behavior. In particular, I have argued that art, religion and science, which are usually seen as achievements that are quite remote from ordinary modes of reasoning, are subserved by evolved cognitive processes that serve functions in everyday cognitive tasks, that arise early and spontaneously in cognitive development, that are shared cross-culturally, and that have evolved in response to selective pressures in our ancestral past. These mundane cognitive processes provide a measuring rod with which we can assess a diversity of cultural phenomena; they form a unified explanatory framework to approach human culture. I have argued that we can explain uncommon thoughts (exceptional human achievements, such as art, religion and science) in terms of interactions between common minds (ordinary human minds that share their knowledge through cultural transmission). This dissertation is subdivided into four parts. Part I outlines the problem of human uniqueness, examining theories on how humans conceptualize the world, and what their mental tool box looks like. Part II discusses the evolutionary and cognitive origins of human artistic behavior. Part III focuses on the cognitive science of religion, especially on how it can be applied to the reasoning of theologians and philosophers of religion. Part IV considers the cognitive basis of scientific practice

    The Morphology and Evolution of the Primate Brachial Plexus

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    Primate evolutionary history is inexorably linked to the evolution of a broad array of locomotor adaptations that have facilitated the clade’s invasion of new niches. Researchers studying the evolution of primates and of their individual locomotor adaptations have traditionally relied on bony morphology – a practical choice given the virtual non-existence of any other type of tissue in the fossil record. However, this focus downplays the potential importance of the many other structures involved in locomotion, such as muscle, cartilage, and neural tissue, which may each be influenced by separate selective forces because of their different roles in facilitating movement. This dissertation is an investigation into the evolution of primate anatomy with an emphasis on the peripheral nervous system, particularly that of the brachial plexus, its intraspecific patterning, and its interactions with muscle in relation to changes in locomotion across clades. As the primate nervous system directs voluntary motor movement to the limbs, thereby facilitating locomotion, its morphology may be expected to vary with primate locomotor proclivities and/or limb anatomy. This prediction has not been explicitly tested. The anatomy of the peripheral nervous system was studied using a comparative approach both within 29 genera of primates and among non-primate clades via extensive primary dissection and a broad literature search in order to better understand its evolution. Data on spinal nerve level contributions, axon combination and branching morphology, nerve distribution pattern, and neural relationships with other soft tissues are detailed with photographs and standardized descriptions for 79 specimens and 123 individual plexuses. 99 characters generated from observations made during dissection were then analyzed using a parsimony-based phylogenetics approach to evaluate the evolutionary patterns presented by the brachial plexus in primates. The phylogenies generated with the brachial plexus characters did not perfectly mirror commonly accepted primate phylogenies, suggesting that while there is some evolutionary signal contained in the plexus, its morphology may also be influenced by forelimb function. As robust hypotheses exist regarding extant primate phylogenetic relationships and evolutionary histories, character evolution was mapped onto existing molecular trees to better understand how the individual structures that comprise the brachial plexus may evolve independently or in concert at different taxonomic levels. The rate of brachial plexus evolution in clades and leaf taxa was then assessed, demonstrating a marked heterogeneity in the structure both within and among clades. Taxa that have undergone recent locomotor shifts since divergence from their most recent common ancestor, and particularly those who exhibit some amount of suspensory behaviors, exhibit the highest rates of evolution observed here. Notably, several ape genera exhibit brachial plexus evolutionary rates significantly higher than the primate mean, running counter to the notion that hominoids have undergone an evolutionary slowdown relative to other primates. As the true unit of homology in the peripheral nervous system is a subject of ongoing debate, several levels of discussion are necessary to understand the variation in primates and their place in the broader spectrum of tetrapod diversity. Macroanatomy, microanatomy, development, and comparative anatomy are explored in a broad context to evaluate the evolutionary trends of the primate peripheral nervous system and are discussed in detail

    Serotonergic modulation of the ventral pallidum by 5HT1A, 5HT5A, 5HT7 AND 5HT2C receptors

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    Introduction: Serotonin's involvement in reward processing is controversial. The large number of serotonin receptor sub-types and their individual and unique contributions have been difficult to dissect out, yet understanding how specific serotonin receptor sub-types contribute to its effects on areas associated with reward processing is an essential step. Methods: The current study used multi-electrode arrays and acute slice preparations to examine the effects of serotonin on ventral pallidum (VP) neurons. Approach for statistical analysis: extracellular recordings were spike sorted using template matching and principal components analysis, Consecutive inter-spike intervals were then compared over periods of 1200 seconds for each treatment condition using a student’s t test. Results and conclusions: Our data suggests that excitatory responses to serotonin application are pre-synaptic in origin as blocking synaptic transmission with low-calcium aCSF abolished these responses. Our data also suggests that 5HT1a, 5HT5a and 5HT7 receptors contribute to this effect, potentially forming an oligomeric complex, as 5HT1a antagonists completely abolished excitatory responses to serotonin application, while 5HT5a and 5HT7 only reduced the magnitude of excitatory responses to serotonin. 5HT2c receptors were the only serotonin receptor sub-type tested that elicited inhibitory responses to serotonin application in the VP. These findings, combined with our previous data outlining the mechanisms underpinning dopamine's effects in the VP, provide key information, which will allow future research to fully examine the interplay between serotonin and dopamine in the VP. Investigation of dopamine and serotonins interaction may provide vital insights into our understanding of the VP's involvement in reward processing. It may also contribute to our understanding of how drugs of abuse, such as cocaine, may hijack these mechanisms in the VP resulting in sensitization to drugs of abuse
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