Relevant bibliographies by topics / Multiple Sclerosis, MRI

Academic literature on the topic 'Multiple Sclerosis, MRI'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "Multiple Sclerosis, MRI"

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Bermel, Robert A., and Robert J. Fox. "MRI IN MULTIPLE SCLEROSIS." CONTINUUM: Lifelong Learning in Neurology 16 (October 2010): 37–57. http://dx.doi.org/10.1212/01.con.0000389933.77036.14.

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Inglese, Matilde, and Maria Petracca. "MRI in multiple sclerosis." Current Opinion in Neurology 31, no. 3 (June 2018): 249–55. http://dx.doi.org/10.1097/wco.0000000000000559.

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Filippi, Massimo, Paolo Preziosa, and Maria A. Rocca. "MRI in multiple sclerosis." Current Opinion in Neurology 31, no. 4 (August 2018): 386–95. http://dx.doi.org/10.1097/wco.0000000000000572.

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Ceccarelli, Antonia, Rohit Bakshi, and Mohit Neema. "MRI in multiple sclerosis." Current Opinion in Neurology 25, no. 4 (August 2012): 402–9. http://dx.doi.org/10.1097/wco.0b013e328354f63f.

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Simon, Jack H. "MRI in Multiple Sclerosis." Physical Medicine and Rehabilitation Clinics of North America 16, no. 2 (May 2005): 383–409. http://dx.doi.org/10.1016/j.pmr.2005.01.012.

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Radü, E. W., N. Mueller-Lenke, A. Thoeni, A. Palatini, and K. Bendfeldt. "MRI in Multiple Sclerosis." Neuroradiology Journal 22, no. 1_suppl (September 2009): 43–50. http://dx.doi.org/10.1177/19714009090220s109.

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The diagnosis of Multiple Sclerosis (MS) is based on clinical findings that are characterized by sudden neurological deficits in different parts of the CNS. Dissemination of lesions in space and time is the basic criterion. MRI can demonstrate most precisely any changes in the water content of brain tissue thus making it a very sensitive diagnostic tool to detect inflammatory processes like MS plaques. The following will briefly summarize the diagnostic features and procedures and will assess the appearance of typical MS lesions, their localization and configuration, which are essential for diagnosis and follow up examinations. It will propose the preferred sequences and technical parameters for standardized baseline examinations and follow-ups.
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Choi, Min Yun, Chang Hyo Sol, Choon Phill Chung, Byung Soo Kim, and Byung Ho Park. "MRI findinga of multiple sclerosis." Journal of the Korean Radiological Society 29, no. 4 (1993): 627. http://dx.doi.org/10.3348/jkrs.1993.29.4.627.

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Lynch, S. G., J. W. Rose, W. Smoker, and J. H. Petajan. "MRI in familial multiple sclerosis." Neurology 40, no. 6 (June 1, 1990): 900. http://dx.doi.org/10.1212/wnl.40.6.900.

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Filippi, Massimo, and Maria A. Rocca. "Conventional MRI in Multiple Sclerosis." Journal of Neuroimaging 17 (April 2007): 3S—9S. http://dx.doi.org/10.1111/j.1552-6569.2007.00129.x.

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Rocca, Maria A., and Massimo Filippi. "Functional MRI in Multiple Sclerosis." Journal of Neuroimaging 17 (April 2007): 36S—41S. http://dx.doi.org/10.1111/j.1552-6569.2007.00135.x.

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Dissertations / Theses on the topic "Multiple Sclerosis, MRI"

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Abdullah, Bassem A. "Segmentation of Multiple Sclerosis Lesions in Brain MRI." Scholarly Repository, 2012. http://scholarlyrepository.miami.edu/oa_dissertations/711.

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Multiple Sclerosis (MS) is an autoimmune disease of central nervous system. It may result in a variety of symptoms from blurred vision to severe muscle weakness and degradation, depending on the affected regions in brain. To better understand this disease and to quantify its evolution, magnetic resonance imaging (MRI) is increasingly used nowadays. Manual delineation of MS lesions in MR images by human expert is time-consuming, subjective, and prone to inter-expert variability. Therefore, automatic segmentation is needed as an alternative to manual segmentation. However, the progression of the MS lesions shows considerable variability and MS lesions present temporal changes in shape, location, and area between patients and even for the same patient, which renders the automatic segmentation of MS lesions a challenging problem. In this dissertation, a set of segmentation pipelines are proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. These techniques use a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The main contribution of this set of frameworks is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional views segmentation to produce verified segmentation. The multi-sectional views pipeline is customized to provide better segmentation performance and to benefit from the properties and the nature of MS lesion in MRI. These customization and enhancement leads to development of the customized MV-T-SVM. The MRI datasets that were used in the evaluation of the proposed pipelines are simulated MRI datasets (3 subjects) generated using the McGill University BrainWeb MRI Simulator, real datasets (51 subjects) publicly available at the workshop of MS Lesion Segmentation Challenge 2008 and real MRI datasets (10 subjects) for MS subjects acquired at the University of Miami. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI.
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Francis, Simon J. "Automatic lesion identification in MRI of multiple sclerosis patients." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82231.

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The object of this thesis is to describe tissue classification software that was developed specifically for the identification of cerebral white matter lesions found in patients with multiple sclerosis (MS). Multiple sclerosis is a debilitating disease of the central nervous system (CNS) which results in a pathology observable macroscopically by magnetic resonance imaging (MRI). Lesion volumes are used as a surrogate of disease progression in clinical trials for MS treatment. The availability of accurate, reliable and reproducible measurements is invaluable in the advancement of patient care and research into this disease. This thesis documents a comprehensive approach to achieve such results which to date has proven to be challenging. A novel fully automated Bayesian classifier was developed which utilizes a variety of techniques to more accurately model brain tissue, and performs lesion identification at a level comparable to human experts. A new validation model that affords a better estimation of ground truth is introduced, providing a better means to measure classification accuracy. It is hoped that this document will be practical in nature, so that people who continue this work will have a step upon which to start.
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Ingle, Gordon Thorpe. "Clinical and MRI features of primary progressive multiple sclerosis." Thesis, University College London (University of London), 2006. http://discovery.ucl.ac.uk/1444980/.

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In approximately 10-15% of cases Multiple Sclerosis follows a progressive rather than a relapsing course and this is known as Primary Progressive Multiple Sclerosis (PPMS). In this thesis previous clinical, pathological and Magnetic Resonance Imaging (MRI) studies of PPMS are reviewed and new studies using two cohorts of patients with PPMS are presented. In the first of these studies an existing cohort of patients with PPMS are re-examined at first two, and then five years, clinically and with MRI, to provide the longest period of MRI follow up in the condition to date. Changes in clinical and MRI measures over this time, and their correlation, are described. Over this extended period, some limited correlation can be found between clinical and MRI measures in PPMS. It is also seen that there is great variability in the rate of MRI and clinical progression between individuals with PPMS, although for a given individual progression is relatively constant. The possible implications of this observation for the nature of the underlying disease process are discussed. The second part of this thesis describes the clinical and MRI features of a second cohort of patients with clinically early PPMS, examined within five years of the first onset of symptoms, the first study to examine this stage of the condition. It is seen that much of the MRI variation seen in established PPMS is already present at this time and that the degree of MRI abnormality, even at this early stage, can be substantial. The specific question as to whether a distinct, early, inflammatory phase occurs in the condition (on the model of the more fully studied relapsing MS subtype) is addressed by the use of triple dose Gadolinium in a subgroup of this cohort examined over six months and evidence for the possible existence of such a phase in some patients with PPMS is found.
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Tench, Christopher. "Diffusion tensor MRI and its application to multiple sclerosis." Thesis, University of Nottingham, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289491.

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Thornton, Helena Barbara. "Cognition and multiple sclerosis: a neuropsychological and MRI study." Thesis, Rhodes University, 1996. http://hdl.handle.net/10962/d1007290.

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Ten people with multiple sclerosis (MS) who felt they had cognitive difficulties because of their MS were investigated. This study had multiple aims. Firstly, to explore the subjective experience of cognitive deficits. Secondly, to assess whether or not there was objective evidence of cognitive difficulties on neuropsychological testing, and whether this was commensurate with a pattern of subcortical dementia. Thirdly, to determine whether their magnetic resonance imaging (MRI) scans replicated the patterns of atrophy frequently reported in MS patients with cognitive difficulties. And finally, to investigate the psychological well-being of the subjects. In depth neuropsychiatric interviews, psychiatric and psychological inventories, a comprehensive neuropsychological battery, and MRI investigations were done. The mean Full Scale Intelligence Quotient (FSIQ) fell within the superior range, at the 89th percentile. On tests of general intelligence, mental state examinations, there was little or no indication of cognitive deterioration. However, on sophisticated neuropsychological testing, there was convincing evidence of cognitive problems. Magnetic resonance imaging lesions were atypical of the reported research on cognitively compromised MS patients.
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Samaraweera, Amal Prasanna Rohan. "MRI white matter lesion central veins in multiple sclerosis." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/44840/.

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This thesis focuses on the use of the Magnetic Resonance Imaging (MRI) white matter lesion (WML) central vein as a biomarker for multiple sclerosis (MS). MS remains a clinical diagnosis, with reliance on MRI to support the diagnosis. Misinterpretation of the MRI can lead to misdiagnoses of diseases that mimic MS. With the increase in disease modifying treatments, accurate and timely diagnosis is needed now more than ever. Using T2* weighted imaging at 3 Tesla (T) MRI, I explored different aspects of WML central veins in patients with relapsing-remitting (RRMS), primary progressive MS (PPMS), and ischaemic small vessel disease (SVD) including: (1) the effect of using different T2* weighted sequences; (2) how T2* and susceptibility weighted imaging (SWI) and fused imaging techniques such as fluid attenuated inversion recovery (FLAIR)-SWI affected the proportion of WML central veins and; (3) determining if WML central veins were as prevalent in patients with PPMS. Further objectives included: (4) attempting to determine if vascular risk factors altered the proportion of WML central veins in patients with MS and; (5) using statistical modelling to calculate a simple diagnostic rule using WML central veins to differentiate MS from SVD. The proportion of WMLs with central veins differed significantly between patients with MS and SVD. Variations of the T2* sequence altered the proportion of WMLs with central veins, but the difference between MS and SVD remained statistically significant. T2* and SWI allowed a higher proportion of WMLs with central veins to be detected, with T2* being just as accurate as FLAIR-SWI in allowing the diagnosis of MS or SVD. Patients with PPMS and RRMS have a similarly high proportion of WMLs with central veins. High sensitivity and specificity for the diagnosis of MS versus SVD can be achieved by identifying a subset of WMLs with central veins. WML central veins could be used as an MRI biomarker using T2* imaging at 3T to differentiate cases of diagnostic uncertainty with RRMS, PPMS and SVD. Application of this imaging technique to patients with diagnostic uncertainty in prospective studies needs to be studied along with refining a clinical diagnostic rule.
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Dixon, Jennifer Elizabeth. "Optimisation of high-field MRI for investigation of multiple sclerosis." Thesis, University of Nottingham, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.523042.

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Ghassemi, Rezwan. "MRI measures of brain injury in children with Multiple Sclerosis." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123023.

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Multiple sclerosis (MS) is thought to be an autoimmune disease that affects the central nervous system of young adults. Although an uncommon disease in children, recent research has examined the effect of this disease upon a younger demographic group. This patient population has attracted the attention of MS researchers, as it promises a better understanding of the pathophysiology of MS at its earliest stage. Magnetic resonance imaging (MRI), a sensitive tool for detecting white matter (WM) pathology, has improved the diagnosis and appreciation of the pathogenesis of MS in adults. However, little is known about its use in children. Therefore, the main objective of this thesis is to contribute and to increase knowledge in this important new area. For this purpose, specific image processing methodologies were developed, and pathology on MRI was compared between patients with adult- and pediatric-onset MS. Comparing the spatial distribution, frequency, and volume of lesions on T2-weighted (T2w) MR images among patients with pediatric- and adult-onset MS, who had similar disease duration, showed a similar total T2w lesions between the two groups. However, children exhibited a higher T2w lesion volume and frequency in the infratentorial region, particularly in the pontine region. Persistent T1-weighted (T1w) lesions, a marker of permanent tissue damage and axonal loss, were assessed to determine whether MS lesions in children are as destructive as those in adults. To obtain a fair comparison using the scans available, normalization of intensity was essential. We showed the limitations of the currently available techniques for intensity normalization, and the need for a WM independent methodology. We proposed and developed a novel WM-independent intensity normalization method for T1w images and assessed inter-scanner, between-scanner and within subject variation before and after normalization. We also calculated the sample size required for detecting recovery of T1w intensity using our methodology and the most commonly used intensity normalization method. Then we used our methodology to assess recovery of normalized T1w intensity within new lesions in children with relapsing remitting MS (RRMS) compared to adults. We found that MS lesions recover better in children, suggesting a greater reparative capacity in younger patients. We also used our intensity normalization method to perform a quantitative comparison of T1w intensity recovery in new lesions between children with MS and children with monophasic inflammatory demyelinating syndromes (monoADS). We found that new MS lesions recover more poorly than of those in children with monoADS. This may suggest that new MS lesions are more destructive than new lesions in monophasic inflammatory demyelinating diseases.
La sclérose en plaques (MS) est considérée comme une maladie auto-immune qui affecte le système nerveux central de l'adulte jeune. Bien que d'une maladie rare chez les enfants, des recherches récentes ont examiné l'effet de cette maladie sur une population plus jeune. Cette population de patients a attiré l'attention des chercheurs en SP, car elle promet une meilleure compréhension de la physiopathologie de la SEP au stade le plus précoce . Imagerie par résonance magnétique (IRM), un outil sensible pour la détection de la substance blanche (WM) pathologie, a amélioré le diagnostic et l'appréciation de la pathogenèse de la SEP chez les adultes. Cependant, peu a été connu au sujet de son utilisation chez les enfants. Par conséquent, l'objectif principal de cette thèse est de contribuer et d'accroître les connaissances dans ce nouveau domaine important. A cet effet, des méthodologies spécifiques de traitement d'image ont été développés, et de la pathologie à l'IRM ont été comparées entre les patients atteints de l'adulte et pédiatrique apparition MS. La comparaison de la répartition spatiale, la fréquence et le volume des lésions sur T2 (en T2) images IRM chez les patients atteints de la SP pédiatrique et adulte-début, qui ont eu la durée de la maladie similaire , ont montré un nombre total de lésions en T2 similaires entre les deux groupes. Cependant, les enfants présentaient un volume plus élevé de lésion en T2 et la fréquence dans la région infratentorial, en particulier dans la région pontique. (T1) des lésions pondérées en T1 persistants, un marqueur des dommages permanents aux tissus et la perte axonale, ont été évalués pour déterminer si les lésions de SP chez les enfants sont aussi destructrices que celles des adultes. Pour obtenir une comparaison équitable en utilisant les analyses disponibles, la normalisation de l'intensité était essentiel. Nous avons montré les limitations des techniques disponibles actuellement pour la normalisation de l'intensité, et le besoin d'une méthode indépendante WM. Nous avons proposé et développé une nouvelle méthode de normalisation de l'intensité WM- indépendante pour les images T1 et évalué inter- scanner, entre - scanner et dans l'objet variation avant et après normalisation. Nous avons également calculé la taille de l'échantillon nécessaire pour détecter la reprise de l'intensité T1w utilisant notre méthodologie et la méthode de normalisation de l'intensité la plus couramment utilisée. Ensuite, nous avons utilisé notre méthode pour tester notre hypothèse et la récupération assesed d'intensité T1w normalisée dans de nouvelles lésions chez les enfants sclérose en plaques rémittente (SEP-RR) par rapport aux adultes. Nous avons constaté que les lésions de SP mieux récupérer les enfants qui peuvent suggérer une plus grande capacité réparatrice chez les patients plus jeunes. Nous avons également utilisé notre méthode de normalisation de l'intensité pour effectuer une comparaison quantitative de la récupération de l'intensité T1w dans de nouvelles lésions entre enfants atteints de SP et les enfants atteints de syndromes inflammatoires démyélinisantes monophasiques (de monoADS). Nous avons constaté que de nouvelles lésions de SP récupérer plus mal que de ceux des enfants avec monoADS. Cela peut suggérer que les lésions New MS sont plus destructeur que de nouvelles lésions dans les maladies démyélinisantes inflammatoires monophasique.
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Edwards, Simon Graeme Mylrea. "MRI volumetric correlates of disease progression and activity in multiple sclerosis." Thesis, Imperial College London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407724.

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Taschler, Bernd. "Spatial point process models for MRI lesion data in multiple sclerosis." Thesis, University of Warwick, 2017. http://wrap.warwick.ac.uk/93636/.

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Over the past three decades neuroimaging techniques in general and magnetic resonance imaging (MRI) in particular have made large contributions to the understanding of human brain function and to the diagnosis and treatment of neurological diseases. One area of wide-spread clinical use of MRI is in the assessment of multiple sclerosis (MS). MS patients present with lesions – areas of decreased neuronal conductivity, akin scarred tissue – that occur across the brain and spinal cord. There has been growing interest to use quantitative measures of lesion incidence, exact lesion location and the shape of lesions in the analysis of MRI-based lesion data. Our objective is to address some of the limitations of current methods which rely on particular assumptions about the data and mostly ignore any spatial correlation and structure in the data. In this work we explore several ways of incorporating multiple sources of information into models that can be used for classification and prediction purposes. We compare and assess different machine learning and Bayesian spatial models in a classification task based on MS lesion data. Furthermore, we propose an extended doubly-stochastic spatial point process model based on Gamma random fields that includes non-imaging data as well as location-specific measures attached to xyz-coordinates, and use both simulated and real data to evaluate our methods.
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Books on the topic "Multiple Sclerosis, MRI"

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Sahraian, M. A. (Mohammad Ali) and SpringerLink (Online service), eds. MRI Atlas of MS Lesions. Berlin, Heidelberg: Springer-Verlag, 2008.

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Esch, Megan, and Nancy L. Sicotte. Neuroimaging in Multiple Sclerosis. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199341016.003.0007.

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Magnetic resonance imaging (MRI) of the brain and spinal cord plays an integral role in establishing the diagnosis of multiple sclerosis (MS). The use of MRI leads to earlier recognition of MS, allowing for earlier treatment initiation and more efficient monitoring of disease treatment and progress. This chapter outlines conventional MRI imaging sequences that are used to evaluate MS white matter lesions in the central nervous system. It also addresses the incorporation of new imaging techniques that have increased understanding of clinically definite MS, its variants, and how various diseases can mimic traditional MS. Finally, it examines novel imaging protocols that have been implemented in MS research, which have elucidated radiographic and pathophysiologic nuances and involvement of deeper central nervous system structures and tracts that play a role in MS progression.
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Absinta, Martina, and Daniel S. Reich. Multiple Sclerosis: MRI and Other Imaging Approaches in MS. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199937837.003.0082.

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Aside from its paramount diagnostic role, imaging techniques, particularly magnetic resonance imaging (MRI), provide unparalleled insights into multiple sclerosis (MS) by assessing the spatiotemporal dynamics of the associated inflammation and neurodegeneration. This dynamical view, predicated on interrogation of individuals with MS at multiple time points, is impossible with pathology. The chapter approaches MRI in MS from this perspective, describing features related to lesion development and location, as well as assessment of global and regional damage. It summarizes current knowledge, addresses the limitations of that knowledge, and suggests ways in which imaging can advance future research.
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Filippi, Massimo, and Maria A. Rocca. Multiple Sclerosis: White Matter versus Gray Matter Involvement (The Cause of Disability in MS). Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199937837.003.0083.

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The classic view of multiple sclerosis (MS) as a chronic, inflammatory-demyelinating condition affecting solely the white matter (WM) of the central nervous system (CNS) has been challenged by the demonstration, from pathologic and magnetic resonance imaging (MRI) studies, of an extensive and diffuse involvement of the gray matter (GM). This observation has driven the application of modern MR technology and methods of analysis to quantify the extent and distribution of damage to the different compartments of the CNS, with the ultimate goal of improving our understanding of the factors associated with the accumulation of clinical disability and cognitive impairment in these patients.
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Alshaikh, Jumana T., Shaan Sudhakaran, and Helene Rubeiz. Trigeminal Neuralgia. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190271787.003.0002.

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Trigeminal neuralgia is characterized by severe, unilateral, paroxysmal stabbing pain affecting the face in the distribution of one of the divisions of the trigeminal nerve. The episodes of pain are brief and are triggered by innocuous physical stimuli. Typical age of onset is the sixth decade, with a female predominance. The most common cause is neurovascular compression. Other causes include multiple sclerosis and structural abnormalities in the cerebellopontine angle. The diagnosis is made clinically, but MRI can be useful in evaluation of the underlying etiology. First-line pharmacotherapy is carbamazepine or oxcarbazepine. If medical therapy fails, procedural interventions should be considered. From ablations to craniotomy, there is an array of procedural treatments available for trigeminal neuralgia. Patients should be educated on the risks and benefits of each procedure prior to pursuing treatment.
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Butler, Reni S. Architectural Distortion (Radial Scar). Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0030.

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Radial scars are benign lesions of the breast characterized pathologically by a fibroelastic core containing entrapped ducts and lobules that radiate outwards in a stellate pattern. This chapter, highlighting radial scar as a cause of architectural distortion, reviews its imaging features and differential diagnosis on mammography, digital breast tomosynthesis, ultrasound, and MRI; its diagnostic workup using multiple modalities; and its histological confirmation with image-guided core needle biopsy. The particular challenge of radial scar presenting as architectural distortion seen only with tomosynthesis is discussed, along with an algorithm for imaging evaluation and biopsy guidance in this setting. As radial scar, which is histologically related to complex sclerosing lesion and radial sclerosing lesion, is considered a high-risk lesion, management recommendations are also reviewed.
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Book chapters on the topic "Multiple Sclerosis, MRI"

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Ingle, G. T., A. J. Thompson, and D. H. Miller. "Conventional MRI." In Primary Progressive Multiple Sclerosis, 63–76. Milano: Springer Milan, 2002. http://dx.doi.org/10.1007/978-88-470-2234-8_8.

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Filippi, M., and M. A. Rocca. "Functional MRI in Multiple Sclerosis." In Normal-appearing White and Grey Matter Damage in Multiple Sclerosis, 145–55. Milano: Springer Milan, 2004. http://dx.doi.org/10.1007/978-88-470-2127-3_13.

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Wishart, Heather A. "Functional MRI of Multiple Sclerosis." In Functional Neuroradiology, 247–60. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-0345-7_13.

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Ge, Yulin, Robert I. Grossman, and E. Mark Haacke. "Susceptibility Weighted Imaging in Multiple Sclerosis." In Susceptibility Weighted Imaging in MRI, 249–64. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470905203.ch15.

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van der Knaap, Marjo S., and Jacob Valk. "Conditions Mimicking Multiple Sclerosis on MRI." In Magnetic Resonance of Myelin, Myelination, and Myelin Disorders, 314–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03078-3_53.

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Rashid, W., and D. H. Miller. "Perfusion MRI." In New Frontiers of MR-based Techniques in Multiple Sclerosis, 73–82. Milano: Springer Milan, 2003. http://dx.doi.org/10.1007/978-88-470-2237-9_6.

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Filippi, M., and M. A. Rocca. "Functional MRI." In New Frontiers of MR-based Techniques in Multiple Sclerosis, 83–97. Milano: Springer Milan, 2003. http://dx.doi.org/10.1007/978-88-470-2237-9_7.

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Gaitán, María I., and Daniel S. Reich. "MRI in Diagnosis and Disease Monitoring." In Multiple Sclerosis and CNS Inflammatory Disorders, 29–44. Chichester, UK: John Wiley & Sons, Ltd., 2014. http://dx.doi.org/10.1002/9781118298633.ch4.

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Wolinsky, J. S., P. A. Narayana, and R. He. "Overview of Treatment Trials: Early Baseline Clinical and MRI Data of the PROMiSe Trial." In Primary Progressive Multiple Sclerosis, 47–61. Milano: Springer Milan, 2002. http://dx.doi.org/10.1007/978-88-470-2234-8_7.

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Filippi, M., and M. A. Rocca. "Diffusion-Weighted MRI." In New Frontiers of MR-based Techniques in Multiple Sclerosis, 33–45. Milano: Springer Milan, 2003. http://dx.doi.org/10.1007/978-88-470-2237-9_4.

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Conference papers on the topic "Multiple Sclerosis, MRI"

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Farias, Fabiano Ricardo, Pedro Costa Klein, Ricardo Bernardi Soder, Jefferson Becker, and Marcio Sarroglia Pinho. "MRI Interpolation for Multiple Sclerosis Lesion Quantification." In 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2016. http://dx.doi.org/10.1109/compsac.2016.159.

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Aslani, Shahab, Vittorio Murino, Michael Dayan, Roger Tam, Diego Sona, and Ghassan Hamarneh. "Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI." In 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). IEEE, 2020. http://dx.doi.org/10.1109/isbi45749.2020.9098721.

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Guerrera, Brittany, Samantha Farrow, Gloria Zeng, and Sally F. Shady. "Multiple Sclerosis Symptom Analyzer." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-66217.

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Multiple Sclerosis (MS) is a chronic neurodegenerative disease of the central nervous system. MS is typically diagnosed between the ages of 20 and 40. There is no known cause of the disease and each individual experiences varying signs and symptoms depending on the severity of their disease. The most common symptoms include tremor, debilitated gait, visual impairment, or cognitive and emotional disturbances. Current methods used to treat MS include oral medication and surgical treatment. The issues with oral medication are the unwanted side effects to otherwise healthy tissue and the lack of patient adherence. Surgical treatment can be invasive and require longer recovery times. An alternate strategy to treat MS is by increasing the knowledge base of the practitioner to potentially treat specific symptoms. Currently, physicians use observations and MRI scans of the brain and spinal cord to help diagnose and track the progression of MS. There are several studies that analyze existing assistive technology to aid in the treatment of MS tremors. Most of these studies did not involve large test groups, therefore it is difficult to prove their validity. Additionally, none of the current devices are able to track symptoms while simultaneously creating medical history records. The goal of the design is to create a new device that will obtain the frequency and amplitude of tremors, while analyzing the effects of temperature and heart rate on the intensity of the tremor. With this data, the device will advance further MS research and lead to better diagnosis and treatment.
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Feis, D. L., H. Neeb, and I. Weinreich. "Wavelet-based Texture Analysis in Multiple Sclerosis using Quantitative MRI." In Signal Processing, Pattern Recognition and Applications. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.678-026.

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Falvo, Antonio, Danilo Comminiello, Simone Scardapane, Michele Scarpiniti, and Aurelio Uncini. "A Multimodal Dense U-Net For Accelerating Multiple Sclerosis MRI." In 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2019. http://dx.doi.org/10.1109/mlsp.2019.8918781.

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Sun, Ming, Zhongyong Tong, Shujun Nie, Miao Yang, and Longzheng Tong. "Investigate the MRI Texture Features of Patients With Multiple Sclerosis." In 2007 IEEE/ICME International Conference on Complex Medical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/iccme.2007.4381843.

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Silveira, Wellington, Rafael Korb, Graçaliz Dimuro, and Rodrigo de Bem. "UniMRI: Unified Repository of Magnetic Resonance Images for Multiple Sclerosis Diagnosis." In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/wvc.2021.18912.

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Multiple sclerosis is an autoimmune disease that affects the central nervous system, destroying myelin. To detect multiple sclerosis, you need to have MRI scans so you can see the areas where myelin has been damaged. This analysis is complex and costly due to the time required to assess injuries. The use of machine learning is desirable as these exams are taken periodically. However, the number of public databases present in the literature containing patients with multiple sclerosis is small when compared to the amount of data needed to train deep neural networks. Thus, the objective of this work is to join public databases of magnetic resonance images existing in the literature, proposing a software library to manipulate and pre-process these data.
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Washimkar, S. P., and S. D. Chede. "Prediction of multiple sclerosis in brain MRI images using hybrid segmentation." In 2017 International Conference on Signal Processing and Communication (ICSPC). IEEE, 2017. http://dx.doi.org/10.1109/cspc.2017.8305845.

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Krishnan, Kalpagam, and M. Stella Atkins. "Segmentation of multiple sclerosis lesions in MRI: an image analysis approach." In Medical Imaging '98, edited by Kenneth M. Hanson. SPIE, 1998. http://dx.doi.org/10.1117/12.310837.

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Sahnoun, Mouna, Fathi Kallel, Mariem Dammak, Omar Kammoun, Chokri Mhiri, Kheireddine Ben Mahfoudh, and Ahmed Ben Hamida. "Contrast-Enhanced Image Analysis for MRI Based Multiple Sclerosis Lesion Segmentation." In 2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP). IEEE, 2020. http://dx.doi.org/10.1109/atsip49331.2020.9231858.

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Reports on the topic "Multiple Sclerosis, MRI"

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Suarez, Ralph O. Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada614005.

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Suarez, Ralph O. Detection of Brain Reorganization in Pediatric Multiple Sclerosis Using Functional MRI. Fort Belvoir, VA: Defense Technical Information Center, October 2015. http://dx.doi.org/10.21236/ada632342.

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Mainero, Caterina. In Vivo Imaging of Cortical Inflammation and Subpial Pathology in Multiple Sclerosis by Combined PET and MRI. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada611615.

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Wu, Xin. The efficacy and safety of anti-CD20 antibody treatments in relapsing multiple sclerosis: a systematic review and network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, June 2022. http://dx.doi.org/10.37766/inplasy2022.6.0075.

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Review question / Objective: The objectives of this systematic review were to evaluate the efficacy and safety of the three existing anti-CD20 antibodies for the treatment of relapsing multiple sclerosis and to aid clinicians in choosing medications. Eligibility criteria: We set the inclusion criteria as follows: (1) study type: RCT; (2) language restriction: only available in English; (3) participants: patients ≥18 years of age diagnosed with relapsing MS, whether with a relapsing–remitting course or a secondary progressive course; (4) intervention: anti-CD20 antibody treatments including ocrelizumab, ofatumumab, rituximab, and corresponding control including placebo and active treatments; (5) outcomes: clinical outcomes including annualized rate of relapse (ARR), the number of patients free of relapse, and the number of patients with confirmed disease progression (CDP); magnetic resonance imaging(MRI) outcomes including gadolinium-enhancing lesion change in T1, change in the volume of lesions on T2, the number of patients with no new or newly enlarged lesions in T2 and the brain volume change (BVC); safety outcomes including adverse events (AEs) and serious adverse events (SAEs). Included RCTs were not requested to supply all the outcomes mentioned above. We set the exclusion criteria as follows: (1) study type: retrospective studies, cohort studies, case reviews and case reports; (2) patients diagnosed with primary progressive MS.
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