Relevant bibliographies by topics / Brain imaging

Academic literature on the topic 'Brain imaging'

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Published: 4 June 2021
Last updated: 28 July 2024

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Journal articles on the topic "Brain imaging"

1

Smolinsky, Mike. "Brain Imaging." Neurology Now 4, no. 4 (July 2008): 11. http://dx.doi.org/10.1097/01.nnn.0000333836.93556.0a.

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2

Goldstein, Sam. "BRAIN IMAGING." Journal of the American Academy of Child & Adolescent Psychiatry 33, no. 5 (June 1994): 762. http://dx.doi.org/10.1097/00004583-199406000-00026.

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Racine, Eric, Ofek Bar-Ilan, and Judy Illes. "Brain Imaging." Science Communication 28, no. 1 (September 2006): 122–43. http://dx.doi.org/10.1177/1075547006291990.

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Gauthier, C. A. "Brain Imaging." TSQ: Transgender Studies Quarterly 1, no. 1-2 (January 1, 2014): 42–45. http://dx.doi.org/10.1215/23289252-2399551.

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Burns, Alistair. "BRAIN IMAGING." Lancet 341, no. 8845 (March 1993): 601–2. http://dx.doi.org/10.1016/0140-6736(93)90360-s.

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Russell, L. Tucker, and R. Gavin Patrick. "Brain Imaging." Veterinary Clinics of North America: Small Animal Practice 26, no. 4 (July 1996): 735–58. http://dx.doi.org/10.1016/s0195-5616(96)50103-8.

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Mitchell, Bradford C. "Brain Imaging." Academic Radiology 17, no. 3 (March 2010): 404. http://dx.doi.org/10.1016/j.acra.2009.08.016.

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Raichle, Marcus E., and Mark A. Mintun. "BRAIN WORK AND BRAIN IMAGING." Annual Review of Neuroscience 29, no. 1 (July 21, 2006): 449–76. http://dx.doi.org/10.1146/annurev.neuro.29.051605.112819.

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Celesia, Gastone G. "Brain Imaging and Brain Function." Journal of Clinical Neurophysiology 3, no. 2 (April 1986): 169. http://dx.doi.org/10.1097/00004691-198604000-00012.

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Holland, Betsy A. "Brain Imaging and Brain Function." Radiology 158, no. 2 (February 1986): 430. http://dx.doi.org/10.1148/radiology.158.2.430.

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Dissertations / Theses on the topic "Brain imaging"

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Liu, Arthur K. (Arthur Kuang-Chung). "Spatiotemporal brain imaging." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8963.

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Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2000.
Includes bibliographical references.
Understanding how the human brain works, in both health and disease, requires data with both high spatial and temporal resolution. This thesis develops and applies a spatiotemporal neuroimaging method. I describe a linear estimation inverse approach, which is a method for the combination of functional magnetic resonance imaging (fMRI) with electroencephalography (EEG) and magnetoencephalography (MEG). fMRI provides millimeter spatial resolution, while EEG and MEG provide millisecond temporal resolution. The thesis is divided into two broad sections: Monte Carlo modeling studies and experimental studies. Improvements to both the bioelectromagnetic forward and inverse solutions are demonstrated. Through modeling studies, I characterize the accuracy of the method with and without functional and anatomic constraints, the effects of various model mis-specifications, and as a function of EEG/MEG sensor configuration. I describe a noise sensitivity normalization to the traditional linear estimation operator that improves the point spread function (a measure of spatial resolution), increases the spatial homogeneity of the point spread, and allows interpretation of the localization in terms of a statistical measure (F-statistic). Using experimentally generated current dipoles implanted an epilepsy patient, I examine the accuracy of both a realistic and spherical EEG head model. This experimental data demonstrates the improved accuracy of the realistic head model, and gives us confidence in using this realistic head model for EEG source localization. The optimized and validated forward and inverse methods are then applied to a variety of empirical measurements. First, the combined multi modality imaging approach is used to simultaneous EEG/fMRI measurements of a visual stimulus, demonstrating the feasibility of measuring and localizing simultaneously acquired electric potential and hemodynamic measurements. Second, combined MEG/fMRI measurements are used to analyze the spatiotemporal characteristics of a cortical network that is responsive to visual motion coherency. Finally, in epilepsy patients, I compare the non-invasive MEG localization of interictal spikes with verification from invasive recordings and surgical results. These studies, in both normal volunteers and patients, clearly demonstrate the utility, accuracy, and power of the combined use of fMRI, EEG and MEG. The tools demonstrated here provide "real time movies" of the human brain at work during a given task or behavior. This information is required to develop computational models of how the human brain/mind works.
by ARthur K. Lui.
Ph.D.
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2

Paolani, Giulia. "Brain perfusion imaging techniques." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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In questo lavoro si sono analizzate due diverse tecniche di imaging di perfusione implementate in Risonanza Magnetica e Tomografia Assiale Computerizzata (TAC). La prima analisi proposta riguarda la tecnica di Arterial Spin Labeling che permette di ottenere informazioni di perfusione senza la somministrazione di un mezzo di contrasto. In questo lavoro si è sviluppata e testata una pipeline completa, attraverso lo sviluppo sia di un protocollo di acquisizione che di post-processing. In particolare, sono stati definiti parametri di acquisizione standard, che permettono di ottenere una buona qualità dei dati, successivamente elaborati attraverso un protocollo di post processing che, a partire dall'acquisizione di un esperimento di ASL, permette il calcolo di una mappa quantitativa di cerebral blood flow (CBF). Nel corso del lavoro, si è notata una asimmetria nella valutazione della perfusione, non giustificata dai dati e probabilmente dovuta ad una configurazione hardware non ottimale. Risolta questa difficoltà tecnica, la pipeline sviluppata sarà utilizzata come standard per l’acquisizione e il post-processing di dati ASL. La seconda analisi riguarda dati acquisiti attraverso esperimenti di perfusione TAC. Si è presa in considerazione la sua applicazione a casi di infarti cerebrali in cui le tecniche di trombectomia sono risultate inefficaci. L'obiettivo di questo lavoro è stata la definizione di una pipeline che permetta il calcolo autonomo delle mappe di perfusione e la standardizzazione della trattazione dei dati. In particolare, la pipeline permette l’analisi di dati di perfusione attraverso l’utilizzo di soli software open-source, contrapponendosi alla metodologia operativa comunemente utilizzata in clinica e rendendo le analisi riproducibili. Il lavoro proposto è inserito in un progetto più ampio, che include future analisi longitudinali con coorti di pazienti più ampie per definire e validare parametri predittivi degli outcome dei pazienti.
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Lawrie, Stephen MacGregor. "Brain imaging in schizophrenia." Thesis, University of Edinburgh, 1997. http://hdl.handle.net/1842/21353.

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Chapter 1 reviews literature, including a systematic and quantitative review of the volumetric MRI studies to date, and examines the links between such biological findings and the clinical features of the illness. Chapter 2 describes an original piece of research designed to examine the biological associations of treatment response in schizophrenia with MRI, SPET and detailed neuropsychological testing. Forty patients were selected as treatment responsive or resistant using standardised criteria. A quantitative analysis of particular regional volumes on MRI revealed that the treatment resistant group had a consistent, but not statistically significant, tendency to smaller cerebral structures. Qualitative ratings showed a tendency to greater atrophy in the treatment resistant patients. The forty SPET scans were subsequently used in a comparison of rCBF in medicated and unmedicated schizophrenia, other psychotic patients and normal controls. The schizophrenic patients showed the predicted hypofrontality, but this was limited to the anterior cingulate and medial pre-frontal cortex. Given some evidence, from post-mortem studies, of a preferential loss of gaba-ergic neurones in the anterior cingulate in schizophrenia, with a compensatory upregulation of non-specific GABA-A receptor binding, a study of GABA receptor binding on SPET was conducted using the benzodiazepine ligand Iomazenil. As described in Chapter 3, the expectation was that Iomazenil binding would be increased in frontal regions, but this was not confirmed in a comparison of ten schizophrenics and ten normal controls; and an apparent reduction of subcortical receptor binding was attributed to methodological problems. Finally, Chapter 4 describes the likely technical and experimental developments in brain imaging studies of schizophrenia in the foreseeable future. Some recommendations are made, based on these advances and the studies described in the thesis, that would help to exploit the full potential of neuroimaging to improve understanding of the pathophysiology of schizophrenia.
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Witzel, Thomas Ph D. Massachusetts Institute of Technology. "Methods for functional brain imaging." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68459.

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Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2011.
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Includes bibliographical references.
Magnetic resonance imaging (MRI) has demonstrated the potential for non-invasive mapping of structure and function (fMRI) in the human brain. In this thesis, we propose a series of methodological developments towards improved fMRI of auditory processes. First, the inefficiency of standard fMRI that acquires brain volumes one slice at a time is addressed. The proposed single-shot method is capable, for the first time, of imaging the entire brain in a single-acquisition while still maintaining adequate spatial resolution for fMRI. This method dramatically increases the temporal resolution of fMRI (20 fold) and improves sampling efficiency as well as the ability to discriminate against detrimental physiological noise. To accomplish this it exploits highly accelerated parallel imaging techniques and MRI signal detection with a large number of coil elements. We then address a major problem in the application of fMVIRI to auditory studies. In standard fMRI, loud acoustic noise is generated by the rapid switching of the gradient magnetic fields required for image encoding, which interferes with auditory stimuli and enforces inefficient and slow sampling strategies. We demonstrate a fMRI method that uses parallel imaging and redesigned gradient waveforms to both minimize and slow down the gradient switching to substantially reduce acoustic noise while still enabling rapid acquisitions for fMRI. Conventional fMRI is based on a hemodynamic response that is secondary to the underlying neuronal activation. In the final contribution of this thesis, a novel image contrast is introduced that is aimed at the direct observation of neuronal magnetic fields associated with functional activation. Early feasibility studies indicate that the imaging is sensitive to oscillating magnetic fields at amplitudes similar to those observed by magnetoencephalography.
by Thomas Witzel.
Ph.D.
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Lin, Fa-Hsuan 1972. "Spatiotemporal brain imaging and modeling." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/18064.

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Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, February 2004.
Includes bibliographical references.
This thesis integrates hardware development, data analysis, and mathematical modeling to facilitate our understanding of brain cognition. Exploration of these brain mechanisms requires both structural and functional knowledge to (i) reconstruct the spatial distribution of the activity, (ii) to estimate when these areas are activated and what is the temporal sequence of activations, and (iii)to determine how the information flows in the large-scale neural network during the execution of cognitive and/or behavioral tasks. Advanced noninvasive medical imaging modalities are able to locate brain activities at high spatial and temporal resolutions. Quantitative modeling of these data is needed to understand how large-scale distributed neuronal interactions underlying perceptual, cognitive, and behavioral functions emerge and change over time. This thesis explores hardware enhancement and novel analytical approaches to improve the spatiotemporal resolution of single (MRI) or combined (MRI/fMRI and MEG/EEG) imaging modalities. In addition, mathematical approaches for identifying large-scale neural networks and their correlation to behavioral measurements are investigated. Part I of the thesis investigates parallel MRI. New hardware and image reconstruction techniques are introduced to improve spatiotemporal resolution and to reduce image distortion in structural and functional MRI. Part II discusses the localization of MEG/EEG signals on the cortical surface using anatomical information from AMTRI, and takes advantage of the high temporal resolution of MEG/EEG measurements to study cortical oscillations in the human auditory system. Part III introduces a multivariate modeling technique to identify "nodes" and "connectivity" in a
(cont.) large-scale neural network and its correlation to behavior measurements in the human motor system.
by Fa-Hsuan Lin.
Ph.D.
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6

Norris, David G. "Diffusion imaging of the brain." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-196833.

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This chapter presents a brief introduction to the application of diffusion-weighted magnetic resonance imaging (MRI) to in vivo studies. Diffusion-weighted MRI has found application both in the clinic, and in basic neuroscience. In the former situation it is primarily used for the detection of brain lesions, in particular infarcted regions. The ability to follow fibre tracts in white matter via diffusion tensor imaging has also made this methodology of interest to the neurosurgeon wishing to avoid severance of essential fibre tracts, but also of interest to the cognitive neuroscientist exploring anatomical connectivity in the brain. The chapter starts with a brief recap of the theory of diffusionweighted MRI and moves on to examine the two major experimental confounds, eddy currents and bulk motion. Current correction schemes for these problems are touched upon. Diffusion anisotropy is introduced as a potential source of artefacts for lesion detection in white matter, and the diffusion tensor model presented. The chapter concludes with a short introduction to fibre tracking.
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Nair, Hemanth P. "Brain imaging of developmental learning effects /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004348.

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Wong, Ho-yin, and 黃浩然. "Disconnectivity in autistic brain." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47326165.

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Autism is a life-long neurodevelopmental condition. Autistic individuals have difficulties in communicative and social ability, and repetitive and stereotypic behavior. It has proposed that these symptoms are caused by underconnectivity in the autistic brain. Functional imaging studies have reported functional underconnectivity in autism. In this thesis, the structural connectivity of the autistic brain was studied. White matter contains axon fibers, which connect different cortical and subcortical brain regions. To measure the structural connectivity, Diffusion tensor imaging (DTI) was applied. Since water diffusion in axons inside the white matter is directional, by measuring the magnitude and direction of water diffusion in white matter, the structural integrity of white matter fibers could be estimated. In this thesis, the background of autism as a genetic, neurological and behavioral condition is outlined. The methods needed to acquire and analyze DTI data are illustrated. A meta-analysis on abnormalities found in autistic brain using DTI was conducted and the most consistently reported regions with DTI differences in autism compared to typically developing controls are described. The results of the metaanalysis were localized to white matter tracts likely to be involved, and the possible associations between anatomy and autistic behavioral features are discussed. Finally, a DTI tractography study was conducted in a sample but clinically representative sample of patients with ASD and eighteen major white matter tracts were explored. Underconnectivity in several tracts was identified. It is hoped that the findings reported here will enhance our understanding of widespread underconnectivity in autism.
published_or_final_version
Psychiatry
Master
Master of Philosophy
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9

Bishop, James Hart. "Imaging Pain And Brain Plasticity: A Longitudinal Structural Imaging Study." ScholarWorks @ UVM, 2017. http://scholarworks.uvm.edu/graddis/786.

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Chronic musculoskeletal pain is a leading cause of disability worldwide yet the mechanisms of chronification and neural responses to effective treatment remain elusive. Non-invasive imaging techniques are useful for investigating brain alterations associated with health and disease. Thus the overall goal of this dissertation was to investigate the white (WM) and grey matter (GM) structural differences in patients with musculoskeletal pain before and after psychotherapeutic intervention: cognitive behavioral therapy (CBT). To aid in the interpretation of clinical findings, we used a novel porcine model of low back pain-like pathophysiology and developed a post-mortem, in situ, neuroimaging approach to facilitate translational investigation. The first objective of this dissertation (Chapter 2) was to identify structural brain alterations in chronic pain patients compared to healthy controls. To achieve this, we examined GM volume and diffusivity as well as WM metrics of complexity, density, and connectivity. Consistent with the literature, we observed robust differences in GM volume across a number of brain regions in chronic pain patients, however, findings of increased GM volume in several regions are in contrast to previous reports. We also identified WM changes, with pain patients exhibiting reduced WM density in tracts that project to descending pain modulatory regions as well as increased connectivity to default mode network structures, and bidirectional alterations in complexity. These findings may reflect network level dysfunction in patients with chronic pain. The second aim (Chapter 3) was to investigate reversibility or neuroplasticity of structural alterations in the chronic pain brain following CBT compared to an active control group. Longitudinal evaluation was carried out at baseline, following 11-week intervention, and a four-month follow-up. Similarly, we conducted structural brain assessments including GM morphometry and WM complexity and connectivity. We did not observe GM volumetric or WM connectivity changes, but we did discover differences in WM complexity after therapy and at follow-up visits. To facilitate mechanistic investigation of pain related brain changes, we used a novel porcine model of low back pain-like pathophysiology (Chapter 6). This model replicates hallmarks of chronic pain, such as soft tissue injury and movement alteration. We also developed a novel protocol to perform translational post-mortem, in situ, neuroimaging in our porcine model to reproduce WM and GM findings observed in humans, followed by a unique perfusion and immersion fixation protocol to enable histological assessment (Chapter 4). In conclusion, our clinical data suggest robust structural brain alterations in patients with chronic pain as compared to healthy individuals and in response to therapeutic intervention. However, the mechanism of these brain changes remains unknown. Therefore, we propose to use a porcine model of musculoskeletal pain with a novel neuroimaging protocol to promote mechanistic investigation and expand our interpretation of clinical findings.
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Cot, Sanz Albert. "Absolute quantification in brain SPECT imaging." Doctoral thesis, Universitat Politècnica de Catalunya, 2003. http://hdl.handle.net/10803/6601.

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Certes malalties neurològiques estan associades amb problemes en els sistemes de neurotransmissió. Una aproximació a l'estudi d'aquests sistemes és la tomografia d'emissió SPECT (Single Photon Emission Computed Tomography) com a tècnica
no-invasiva que proporciona imatges funcionals representatives de l'activitat neuronal. Aquesta tècnica permet la visualització i l'anàlisi de diferents òrgans i teixits dins l'àmbit de la Medicina Nuclear.

Malgrat que la inspecció visual de la imatge a vegades és suficient per establir el diagnòstic, la quantificació dels paràmetres de la imatge reconstruida poden millorar la fiabilitat i exactitud del diagnòstic precoç de la malaltia. En particular, la quantificació d'estudis de neurotransmissors de dopamina pot ajudar a detectar els estadis inicials de malalties com el Parkinson. Així mateix, la quantificació permet un seguiment més acurat de l'evolució de la malaltia i una evaluació dels efectes de la terapèutica aplicada.

La quantificació es veu afectada pels efectes degradants de la imatge com són el soroll estadístic, la resposta del sistema col.limador/detector i l'efecte de dispersió i/o atenuació dels fotons en la seva interacció amb la matèria. Alguns d'aquests efectes poden ser corregits mitjançant l'ús d'algoritmes de reconstrucció iteratius.

L'objectiu d'aquesta tesi és aconseguir una quantificació tant absoluta com relativa dels valors numèrics de la imatge reconstruida de manera que reprodueixin la distribució d'activitat real del pacient en el moment de l'adquisició de l'estudi de SPECT. Per aconseguir-ho s'han desenvolupat diferents codis i algoritmes per millorar els mètodes de reconstrucció existents i validar-ne els seus resultats.

La validació i millora dels algoritmes s'ha basat en l'ús de tècniques de simulació Monte Carlo. S'han analitzat els diferents codis Monte Carlo disponibles en l'àmbit de la Medicina Nuclear i s'ha escollit SimSET. La interpretació dels resultats obtinguts i la comparació amb els resultats experimentals ens van dur a incorporar modificacions en el codi original. D'aquesta manera vam obtenir i validar SimSET com a generador d'estudis de SPECT a partir de pacients i objectes virtuals.

La millora dels algoritmes es va basar en la incorporació de models analítics de la resposta del sistema col.limador/detector. La modelització del sistema es va implementar per diferents configuracions i energies de la font amb la utilització del codi Monte Carlo PENELOPE. Així mateix es va dissenyar un nou algoritme iteratiu que incorporés l'efecte 3D del sistema i es va tenir en compte la valoració de la imatge en tot el seu volum.

Finalment, es va proposar una correcció de l'scattering utilitzant el simulador SimSET modificat per tal d'accelerar el procés de reconstrucció. Els valors reconstruits de la imatge ens han permès recuperar més d'un 95\% dels valors originals, permetent per tant la quantificació absoluta de les imatges de SPECT.
Many forms of brain diseases are associated with problems in the neurotransmission systems. One approach to the assessment of such systems is the use of Single Photon Emission Computed Tomography (SPECT) brain imaging. Neurotransmission SPECT has become an important tool in neuroimaging and is today regarded as a useful method in both clinical and basic research. SPECT is able to non-invasively visualize and analyze different organs and tissues functions or properties in Nuclear Medicine.

Although visual inspection is often sufficient to assess neurotransmission imaging, quantification might improve the diagnostic accuracy of SPECT studies of the dopaminergic system. In particular, quantification of neurotransmission SPECT studies in Parkinson Disease could help us to diagnose this illness in the early pre-clinical stages. One of the main research topics in SPECT is to achieve early diagnosis, indeed preclinical diagnosis in neurodegenerative illnesses. In this field detailed analysis of shapes and values of the region of interest (ROIs) of the image is important, thus quantification is needed. Moreover, quantification allows a follow-up of the progression of disease and to assess the effects of potential neuroprotective treatment strategies. Therefore, the aim of this thesis is to achieve quantification of both the absolute activity values and the relative values of the reconstructed SPECT images.

Quantification is affected by the degradation of the image introduced by statistical noise, attenuation, collimator/detector response and scattering effects. Some of these degradations may be corrected by using iterative reconstruction algorithms, which thus enable a more reliable quantification. The importance of correcting degradations in reconstruction algorithms to improve quantification accuracy of brain SPECT studies has been proved.

Monte Carlo simulations are the --gold standard' for testing reconstruction algorithms in Nuclear Medicine. We analyzed the available Monte Carlo codes and we chose SimSET as a virtual phantom simulator. A new stopping criteria in SimSET was established in order to reduce the simulation time. The modified SimSET version was validated as a virtual phantom simulator which reproduces realistic projection data sets in SPECT studies.

Iterative algorithms permit modelling of the projection process, allowing for correction of spatially variant collimator response and the photon crosstalk effect between transaxial slices. Thus, our work was focused on the modelling of the collimator/detector response for the parallel and fan beam configurations using the Monte Carlo code PENELOPE. Moreover, a full 3D reconstruction with OS-EM algorithms was developed.

Finally, scattering has recognized to be one of the most significant degradation effects in SPECT quantification. Nowadays this subject is an intensive field of research in SPECT techniques. Monte Carlo techniques appear to be the most reliable way to include this correction. The use of the modified SimSET simulator accelerates the forward projection process although the computational burden is already a challenge for this technique.

Full 3D reconstruction simultaneously applied with Monte Carlo-based scattering correction and the 3D evaluation procedure is a major upgrade technique in order to obtain valuable, absolute quantitative estimates of the reconstructed images. Once all the degrading effects were corrected, the obtained values were 95\% of the theoretical values. Thus, the absolute quantification was achieved.
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Books on the topic "Brain imaging"

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Wagner, Henry N. Brain Imaging. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-308-8.

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1921-, Sokoloff Louis, and Association for Research in Nervous and Mental Disease., eds. Brain imaging and brain function. New York: Raven Press, 1985.

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Weis, Serge, Michael Sonnberger, Andreas Dunzinger, Eva Voglmayr, Martin Aichholzer, Raimund Kleiser, and Peter Strasser. Imaging Brain Diseases. Vienna: Springer Vienna, 2019. http://dx.doi.org/10.1007/978-3-7091-1544-2.

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Hyder, Fahmeed, ed. Dynamic Brain Imaging. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-543-5.

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Sekihara, Kensuke, and Srikantan S. Nagarajan. Electromagnetic Brain Imaging. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14947-9.

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Hattingen, Elke, and Ulrich Pilatus, eds. Brain Tumor Imaging. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-642-45040-2.

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Gert, Pfurtscheller, and Lopes da Silva, F. H., 1935-, eds. Functional brain imaging. Toronto: Hans Huber Publishers, 1988.

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Polzehl, Jörg, and Karsten Tabelow. Magnetic Resonance Brain Imaging. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29184-6.

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Pillai, Jay J., ed. Functional Brain Tumor Imaging. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4419-5858-7.

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Shôn, Lewis, and Higgins Nicholas, eds. Brain imaging in psychiatry. Oxford [England]: Blackwell Science, 1996.

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Book chapters on the topic "Brain imaging"

1

Tyrer, Peter J., Mark Slifstein, Joris C. Verster, Kim Fromme, Amee B. Patel, Britta Hahn, Christer Allgulander, et al. "Brain Imaging." In Encyclopedia of Psychopharmacology, 250. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_4098.

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Wideman, Timothy H., Michael J. L. Sullivan, Shuji Inada, David McIntyre, Masayoshi Kumagai, Naoya Yahagi, J. Rick Turner, et al. "Brain Imaging." In Encyclopedia of Behavioral Medicine, 252. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_100205.

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Beaton, Elliott A. "Brain, Imaging." In Encyclopedia of Behavioral Medicine, 295–99. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1101.

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Wideman, Timothy H., Michael J. L. Sullivan, Shuji Inada, David McIntyre, Masayoshi Kumagai, Naoya Yahagi, J. Rick Turner, et al. "Brain, Imaging." In Encyclopedia of Behavioral Medicine, 256–59. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1101.

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Panda, Satyajit, and Sagarika Mahapatro. "Brain Imaging." In Encyclopedia of Evolutionary Psychological Science, 1–8. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-16999-6_2222-1.

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Rosenberg, David R., Phillip C. Easter, and Georgia Michalopoulou. "Brain Imaging." In Obsessive-Compulsive Disorder, 244–76. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119941125.ch10.

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Foster, Nina. "Brain Imaging." In Encyclopedia of Child Behavior and Development, 289–90. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-79061-9_415.

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Panda, Satyajit, and Sagarika Mahapatro. "Brain Imaging." In Encyclopedia of Evolutionary Psychological Science, 745–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-19650-3_2222.

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McKinney, Alexander M., Yang Wang, and Ze Zhang. "Brain." In Classic Imaging Signs, 9–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56348-6_2.

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Crispino, Mario, and Emanuela Crispino. "Brain." In Atlas of Imaging Anatomy, 1–27. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10750-9_1.

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Conference papers on the topic "Brain imaging"

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Valentino, D. J., J. C. Mazziotta, and H. K. Huang. "Mapping Brain Function To Brain Anatomy." In Medical Imaging II, edited by Roger H. Schneider and Samuel J. Dwyer III. SPIE, 1988. http://dx.doi.org/10.1117/12.968665.

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Takehara, Hiroaki, Makito Haruta, Yasumi Ohta, Mayumi Motoyama, Toshihiko Noda, Kiyotaka Sasagawa, Takashi Tokuda, and Jun Ohta. "Implantable semiconductor imaging devices for in vivo optical imaging of brain." In Optics and the Brain. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/brain.2015.brw1b.3.

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Culver, Joseph P. "Optical Imaging of Functional Connectivity." In Optics and the Brain. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/brain.2015.brm4b.1.

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Zilpelwar, Sharvari, Xiaojun Cheng, and David A. Boas. "Interferometric dynamic laser speckle imaging." In Optics and the Brain. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/brain.2023.bth1b.2.

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We developed interferometric dynamic laser speckle imaging (iDLSI) capable of three-dimensional volumetric measurements of the blood flow. Here, we present the numerical and analytical model for g2,iDLSI(τ) and perform preliminary measurement in the mouse brain.
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Safi, Abdul Mohaimen, Cesar Hernandez-Isidro, Stephen Cini, Sadhu Moka, Mitchell Harrah, Christopher L. Passaglia, and Ashwin B. Parthasarathy. "Quantitative Cerebral Blood Flow Imaging with Synthetic Single-Shot Multi-Exposure Laser Speckle Imaging." In Optics and the Brain. Washington, D.C.: OSA, 2021. http://dx.doi.org/10.1364/brain.2021.bw3b.4.

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Li, Hongming, and Yong Fan. "Functional brain atlas construction for brain network analysis." In SPIE Medical Imaging, edited by Sebastien Ourselin and David R. Haynor. SPIE, 2013. http://dx.doi.org/10.1117/12.2007394.

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Valentino, D. J., P. D. Cutler, J. C. Mazziotta, H. K. Huang, R. A. Drebin, and C. A. Pelizzari. "Volumetric Display of Brain Function and Brain Anatomy." In 1989 Medical Imaging, edited by Samuel J. Dwyer III, R. Gilbert Jost, and Roger H. Schneider. SPIE, 1989. http://dx.doi.org/10.1117/12.976455.

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Guo, Ruipeng, and Rajesh Menon. "Computational cannula-based microscopy for brain imaging." In Computational Optical Sensing and Imaging. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cosi.2022.ctu5f.3.

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With Machine Learning (ML) algorithms, we experimentally demonstrated deep imaging inside mice brains with cellular-level resolution using computational cannula microscopy. Multi-ANNs were used for the prediction of brain images.
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Crair, Michael. "Multiscale Imaging of Activity in Cortex." In Optics and the Brain. Washington, D.C.: OSA, 2017. http://dx.doi.org/10.1364/brain.2017.brs1b.1.

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Wang, Yaping, Gang Li, Jingxin Nie, Pew-Thian Yap, Lei Guo, and Dinggang Shen. "Consistent 4D brain extraction of serial brain MR images." In SPIE Medical Imaging, edited by Sebastien Ourselin and David R. Haynor. SPIE, 2013. http://dx.doi.org/10.1117/12.2006651.

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Reports on the topic "Brain imaging"

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Wood, C. C. Electromagnetic inverse applications for functional brain imaging. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/534510.

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Limperopoulos, Catherine. Advanced Pediatric Brain Imaging Research and Training Program. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada614550.

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Limperopoulos, Catherine. Advanced Pediatric Brain Imaging Research and Training Program. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada570521.

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Limperopoulos, Catherine. Advanced Pediatric Brain Imaging Research and Training Program. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada592842.

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Gullapalli, Rao P. Evaluation of Diffusion Kurtosis Imaging in Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, May 2013. http://dx.doi.org/10.21236/ada610706.

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Fowler, Joanna S., and Michael Furey. Radiotracer Synthesis and PET Imaging Evaluation for Brain Histamine Receptors. Office of Scientific and Technical Information (OSTI), August 2014. http://dx.doi.org/10.2172/1149990.

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Haacke, E. M. Development of Magnetic Resonance Imaging Biomarkers for Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada601794.

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Haacke, Ewart M. Development of Magnetic Resonance Imaging Biomarkers for Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada601883.

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Just, Marcel A. Parallel Supercomputing in Cognitive Brain Imaging Other Massive 3-D Dataspaces. Fort Belvoir, VA: Defense Technical Information Center, December 1999. http://dx.doi.org/10.21236/ada374854.

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Keltner, John Robinson. Triple-quantum filtered NMR imaging of sodium in the human brain. Office of Scientific and Technical Information (OSTI), April 1993. http://dx.doi.org/10.2172/10184286.

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