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Articles Published Processes
9/15/2014 4:38:00 PM | Browse: 1148 | Download: 1125
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Received |
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2013-11-13 08:07 |
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Peer-Review Started |
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2013-11-14 09:44 |
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To Make the First Decision |
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2013-12-25 18:06 |
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Return for Revision |
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2013-12-31 14:47 |
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Revised |
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2014-01-23 20:25 |
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Second Decision |
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2014-03-18 15:00 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2014-03-18 15:23 |
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Articles in Press |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2014-04-09 16:08 |
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Typeset the Manuscript |
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2014-04-23 08:16 |
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Publish the Manuscript Online |
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2014-04-25 18:26 |
Category |
Radiology, Nuclear Medicine & Medical Imaging |
Manuscript Type |
Topic Highlights |
Article Title |
Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques
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Manuscript Source |
Invited Manuscript |
All Author List |
Evangelia Tsolaki, Evanthia Kousi, Patricia Svolos, Efthychia Kapsalaki, Kyriaki Theodorou, Constastine Kappas and Ioannis Tsougos |
Funding Agency and Grant Number |
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Corresponding Author |
Ioannis Tsougos, MSc, PhD, Assistant Professor in Medical Physics Department, University of Thessaly, Panepistimiou 2, Biopolis, 41110 Larissa, Greece. tsougos@med.uth.gr |
Key Words |
Decision support systems; Magnetic resonance imaging; Magnetic resonance spectroscopy; Diffusion weighted imaging; Diffusion tensor imaging; Perfusion weighted imaging; Pattern recognition |
Core Tip |
The quantification of the imaging profile of brain neoplasms by combining conventional magnetic resonance imaging and advanced imaging techniques introduces critical underlying pathophysiological information which seems to be the key to success. Thus, it is evident that the pursuit of this goal should be oriented towards the development of decision support software that will utilize large amounts of clinical data with extremely significant diagnostic value which often remain unexploited, hence resulting in a more valid and precise method of differential diagnosis and the selection of the most successful treatment scheme. |
Publish Date |
2014-04-25 18:26 |
Citation |
Tsolaki E, Kousi E, Svolos P, Kapsalaki E, Theodorou K, Kappas C, Tsougos I. Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques. World J Radiol 2014; 6(4): 72-81 |
URL |
http://www.wjgnet.com/1949-8470/full/v6/i4/72.htm |
DOI |
http://dx.doi.org/10.4329/wjr.v6.i4.72 |
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