Simultaneous assessment of regional distributions of atrophy across the neuraxis in MS patients

Autor: Patrick Freund, Nico Papinutto, Antje Bischof, Michela Azzarito, Gina Kirkish, John Ashburner, Alan Thompson, Stephen L. Hauser, Roland G. Henry

Publikováno v: NeuroImage: Clinical, Vol 34, Iss , Pp 102985- (2022)

Background: The ability to assess brain and cord atrophy simultaneously would improve the efficiency of MRI to track disease evolution. Objective: To test a promising tool to simultaneously map the regional distribution of atrophy in multiple scleros

Externí odkaz: https://doaj.org/article/7cf4f4dd6f664e879899cb03974314cf

Simultaneous voxel‐wise analysis of brain and spinal cord morphometry and microstructure within the SPM framework

Autor: Michela Azzarito, Yaël Balbastre, John Ashburner, Patrick Freund, Martina F. Callaghan, Maryam Seif, Claudia Blaiotta, Sreenath Pruthviraj Kyathanahally

Publikováno v: Human Brain Mapping

To validate a simultaneous analysis tool for the brain and cervical cord embedded in the statistical parametric mapping (SPM) framework, we compared trauma‐induced macro‐ and microstructural changes in spinal cord injury (SCI) patients to control

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96b3bbbe3ad1d48714c713455ed17c88
http://europepmc.org/articles/PMC7721239

Model-based multi-parameter mapping

Autor: John Ashburner, Yaël Balbastre, Michela Azzarito, Mikael Brudfors, Martina F. Callaghan, Christian Lambert

Publikováno v: Medical Image Analysis

Highlights • Model-based estimation of quantitative multi-parameter maps. • Maximum-likelihood or Maximum a posteriori solutions. • Embedded denoising using a joint total-variation prior. • Stable second-order solver using a novel approximate

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e807b9dc0287dea1e6765b706e5e23d7
http://arxiv.org/abs/2102.01604

Slow conduction in mixed cultured strands of primary ventricular cells and stem cell-derived cardiomyocytes

Autor: Nina D. Ullrich, Irene C. Marcu, Jan P. Kucera, Yann Prudat, Michela Azzarito

Publikováno v: Frontiers in Cell and Developmental Biology, Vol 3 (2015)
Kucera, Jan; Prudat, Yann; Marcu, Irene Cristina; Azzarito, Michela; Ullrich, Nina (2015). Slow conduction in mixed cultured strands of primary ventricular cells and stem cell-derived cardiomyocytes. Frontiers in cell and developmental biology, 3, p. 58. Frontiers 10.3389/fcell.2015.00058
Frontiers in cell and developmental biology
Frontiers in Cell and Developmental Biology

Modern concepts for the treatment of myocardial diseases focus on novel cell therapeutic strategies involving stem cell-derived cardiomyocytes (SCMs). However, functional integration of SCMs requires similar electrophysiological properties as primary

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7bd5021f085a5dfe2be4ad1f4d4e6f42
http://journal.frontiersin.org/Journal/10.3389/fcell.2015.00058/full

Quantifying Progression of Multiple Sclerosis via Classification of Depth Videos

Autor: Peter Kontschieder, Jessica Burggraaff, Darko Zikic, Antonio Criminisi, Thomas Vogel, Christian P. Kamm, Jonas F. Dorn, Robert Corish, Michela Azzarito, Cecily Morrison, Chris H. Polman, Ludwig Kappos, Marcus D’Souza, Prejaas Tewarie, Abigail Sellen, Ben Glocker, Bernard M. J. Uitdehaag, Peter Chin, Frank Dahlke

Publikováno v: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 ISBN: 9783319104690
MICCAI (2)
Scopus-Elsevier
Kontschieder, P, Dorn, J F, Morrison, C, Corish, R, Zikic, D, Sellen, A, D'Souza, M, Kamm, C P, Burggraaff, J, Tewarie, P K, Vogel, T, Azzarito, M, Glocker, B, Chin, P, Dahlke, F, Polman, C H, Kappos, L, Uitdehaag, B M J & Criminisi, A 2014, Quantifying progression of multiple sclerosis via classification of depth videos . in Medical image computing and computer-assisted intervention – MICCAI 2014 . Lecture Notes in Computer Science, Springer International Publishing, pp. 429-437 . https://doi.org/10.1007/978-3-319-10470-6_54
Medical image computing and computer-assisted intervention – MICCAI 2014, 429-437
STARTPAGE=429;ENDPAGE=437;TITLE=Medical image computing and computer-assisted intervention – MICCAI 2014

This paper presents new learning-based techniques for measuring disease progression in Multiple Sclerosis (MS) patients. Our system aims to augment conventional neurological examinations by adding quantitative evidence of disease progression. An off-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3cb31a5986393ea43e70e6761f69773
https://doi.org/10.1007/978-3-319-10470-6_54