Výsledky vyhledávání - "Francesco Sforazzini"

Akademický článek

Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition

Autor: Phillip G.D. Ward, Edwina R. Orchard, Stuart Oldham, Aurina Arnatkevičiūtė, Francesco Sforazzini, Alex Fornito, Elsdon Storey, Gary F. Egan, Sharna D. Jamadar

Publikováno v: NeuroImage, Vol 221, Iss , Pp 117196- (2020)

Resting-state connectivity measures the temporal coherence of the spontaneous neural activity of spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in the relative concentra

Externí odkaz: https://doaj.org/article/946178810f8a4d629069cb0b1a9bdeff

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Akademický článek

Relationship between parenthood and cortical thickness in late adulthood.

Autor: Edwina R Orchard, Phillip G D Ward, Francesco Sforazzini, Elsdon Storey, Gary F Egan, Sharna D Jamadar

Publikováno v: PLoS ONE, Vol 15, Iss 7, p e0236031 (2020)

Pregnancy and the early postpartum period alter the structure of the brain; particularly in regions related to parental care. However, the enduring effects of this period on human brain structure and cognition in late life is unknown. Here we use mag

Externí odkaz: https://doaj.org/article/094f91962fce48cba6110a0b93097d80

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Akademický článek

Accurate hybrid template–based and MR-based attenuation correction using UTE images for simultaneous PET/MR brain imaging applications

Autor: Jakub Baran, Zhaolin Chen, Francesco Sforazzini, Nicholas Ferris, Sharna Jamadar, Ben Schmitt, David Faul, Nadim Jon Shah, Marian Cholewa, Gary F. Egan

Publikováno v: BMC Medical Imaging, Vol 18, Iss 1, Pp 1-16 (2018)

Abstract Background Attenuation correction is one of the most crucial correction factors for accurate PET data quantitation in hybrid PET/MR scanners, and computing accurate attenuation coefficient maps from MR brain acquisitions is challenging. Here

Externí odkaz: https://doaj.org/article/7a0671a849f14b45b23fb11e13e0c764

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MR-Class: A Python Tool for Brain MR Image Classification Utilizing One-vs-All DCNNs to Deal with the Open-Set Recognition Problem

Autor: Patrick Salome, Francesco Sforazzini, Gianluca Brugnara, Andreas Kudak, Matthias Dostal, Christel Herold-Mende, Sabine Heiland, Jürgen Debus, Amir Abdollahi, Maximilian Knoll

Publikováno v: Cancers; Volume 15; Issue 6; Pages: 1820

Background: MR image classification in datasets collected from multiple sources is complicated by inconsistent and missing DICOM metadata. Therefore, we aimed to establish a method for the efficient automatic classification of MR brain sequences. Met

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MR Intensity Normalization Methods Impact Sequence Specific Radiomics Prognostic Model Performance in Primary and Recurrent High-Grade Glioma

Autor: Patrick Salome, Francesco Sforazzini, Gianluca Brugnara, Andreas Kudak, Matthias Dostal, Christel Herold-Mende, Sabine Heiland, Jürgen Debus, Amir Abdollahi, Maximilian Knoll

Publikováno v: Cancers; Volume 15; Issue 3; Pages: 965

Purpose: This study investigates the impact of different intensity normalization (IN) methods on the overall survival (OS) radiomics models’ performance of MR sequences in primary (pHGG) and recurrent high-grade glioma (rHGG). Methods: MR scans acq

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62827c768ba17d5a7777e5a5a37ab69f

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A Comprehensive Framework to Capture the Arcana of Neuroimaging Analysis

Autor: Thomas G. Close, Phillip G. D. Ward, Zhaolin Chen, Wojtek Goscinski, Francesco Sforazzini, Gary F. Egan

Publikováno v: Neuroinformatics. 18:109-129

Mastering the “arcana of neuroimaging analysis”, the obscure knowledge required to apply an appropriate combination of software tools and parameters to analyse a given neuroimaging dataset, is a time consuming process. Therefore, it is not typica

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb2b42536ba8696f388a31198212f14a
https://doi.org/10.1007/s12021-019-09430-1

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Simultaneous task-based BOLD-fMRI and [18-F] FDG functional PET for measurement of neuronal metabolism in the human visual cortex

Autor: Zhaolin Chen, Sharna D. Jamadar, Francesco Sforazzini, Shenpeng Li, Jakub Baran, Gary F. Egan, Phillip G. D. Ward

Publikováno v: NeuroImage. 189:258-266

Studies of task-evoked brain activity are the cornerstone of cognitive neuroscience, and unravel the spatial and temporal brain dynamics of cognition in health and disease. Blood oxygenation level dependent functional magnetic resonance imaging (BOLD

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e70e38e475c57a07b4b400a1eef0fbbf
https://doi.org/10.1016/j.neuroimage.2019.01.003

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Deep Learning–based Automatic Lung Segmentation on Multiresolution CT Scans from Healthy and Fibrotic Lungs in Mice

Autor: Francesco Sforazzini, Patrick Salome, Mahmoud Moustafa, Cheng Zhou, Christian Schwager, Katrin Rein, Nina Bougatf, Andreas Kudak, Henry Woodruff, Ludwig Dubois, Philippe Lambin, Jürgen Debus, Amir Abdollahi, Maximilian Knoll

Publikováno v: Radiology: Artificial Intelligence 4(2):e210095
Radiology: Artificial Intelligence, 4(2):210095. Radiological Society of North America, Inc.

Purpose: To develop a model to accurately segment mouse lungs with varying levels of fibrosis and investigate its applicability to mouse images with different resolutions.Materials and Methods: In this experimental retrospective study, a U-Net was tr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11694974cf2e590c250580f4622e7fc0

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