Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia. - Wikidata - awgldk - TriplyDB

Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia.

Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia.

http://www.wikidata.org/entity/Q34712689

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Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses - the case of behavioral variant frontotemporal dementia.Clinical applications of PET/MRI: current status and future perspectives.Neuroimaging characteristics of dementia with Lewy bodies.Current status and future role of brain PET/MRI in clinical and research settings.Recent imaging advances in neurology.How far is arterial spin labeling MRI from a clinical reality? Insights from arterial spin labeling comparative studies in Alzheimer's disease and other neurological disorders.Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias.Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.Disentangling the neural correlates of corticobasal syndrome and corticobasal degeneration with systematic and quantitative ALE meta-analyses Reference cluster normalization improves detection of frontotemporal lobar degeneration by means of FDG-PET.Dissociating memory networks in early Alzheimer's disease and frontotemporal lobar degeneration - a combined study of hypometabolism and atrophy.Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease Feasibility of simultaneous whole-brain imaging on an integrated PET-MRI system using an enhanced 2-point Dixon attenuation correction method.Imaging biomarkers associated with cognitive decline: a review.Identification of MCI individuals using structural and functional connectivity networks Executive deficits are related to the inferior frontal junction in early dementia.Diagnostic neuroimaging across diseases.OPTIMIZING DIAGNOSIS AND MANANGEMENT IN MILD-TO-MODERATE ALZHEIMER'S DISEASE.Predicting behavioral variant frontotemporal dementia with pattern classification in multi-center structural MRI data.A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.Integrated (18)F-fluorodeoxyglucose positron emission tomography magnetic resonance imaging ((18)F-FDG PET/MRI), a multimodality approach for comprehensive evaluation of dementia patients: A pictorial essay.Reprint of "Quantitative evaluation of brain development using anatomical MRI and diffusion tensor imaging".Applying Automated MR-Based Diagnostic Methods to the Memory Clinic: A Prospective Study.Relationship between imaging biomarkers, age, progression and symptom severity in Alzheimer's disease.Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD.Molecular and metabolic pattern classification for detection of brain glioma progression.Disease-Specific Regions Outperform Whole-Brain Approaches in Identifying Progressive Supranuclear Palsy: A Multicentric MRI Study.Combined Imaging Markers Dissociate Alzheimer's Disease and Frontotemporal Lobar Degeneration - An ALE Meta-Analysis Combined PET/MRI: Multi-modality Multi-parametric Imaging Is Here: Summary Report of the 4th International Workshop on PET/MR Imaging; February 23-27, 2015, Tübingen, Germany.Multi-Kernel Learning with Dartel Improves Combined MRI-PET Classification of Alzheimer's Disease in AIBL Data: Group and Individual Analyses.Imaging and fluid biomarkers in frontotemporal dementia.Mapping brain morphological and functional conversion patterns in predementia late-onset bvFTD.Accurate Prediction of Conversion to Alzheimer's Disease using Imaging, Genetic, and Neuropsychological Biomarkers.Identification of Conversion from Normal Elderly Cognition to Alzheimer's Disease using Multimodal Support Vector Machine.Combined PET/MR: The Real Work Has Just Started. Summary Report of the Third International Workshop on PET/MR Imaging; February 17-21, 2014, Tübingen, Germany Neural correlates of the DemTect in Alzheimer's disease and frontotemporal lobar degeneration - A combined MRI & FDG-PET study Using simultaneous PET/MRI to compare the accuracy of diagnosing frontotemporal dementia by arterial spin labelling MRI and FDG-PET.PET/MR Imaging: New Frontier in Alzheimer's Disease and Other Dementias.Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.

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P2860

Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia.

http://www.wikidata.org/entity/Q34712689

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Combined evaluation of FDG-PET ...... d differentiation of dementia.

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Combined evaluation of FDG-PET ...... d differentiation of dementia.

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Combined evaluation of FDG-PET ...... d differentiation of dementia.

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Combined evaluation of FDG-PET ...... d differentiation of dementia.

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Combined evaluation of FDG-PET ...... d differentiation of dementia.

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Harald E Möller

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Henryk Barthel

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Juergen Dukart

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P2860

Neural correlates of Alzheimer's disease and mild cognitive impairment: a systematic and quantitative meta-analysis involving 1351 patients

“Mini-mental state”

Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease

A fast diffeomorphic image registration algorithm

Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria

Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria

Unified segmentation

The Clinical Dementia Rating (CDR): current version and scoring rules

Towards a nosology for frontotemporal lobar degenerations-a meta-analysis involving 267 subjects.

Structural and functional biomarkers of prodromal Alzheimer's disease: a high-dimensional pattern classification study.

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Annette Horstmann

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