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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Конспект

Radiomics represents an innovative approach to medical image analysis, enabling comprehensive quantitative evaluation of radiological images through advanced image processing and Machine or Deep Learning algorithms. This technique uncovers intricate data patterns beyond human visual detection. Traditionally, executing a radiomic pipeline involves multiple standardized phases across several software platforms. This could represent a limit that was overcome thanks to the development of the matRadiomics application. MatRadiomics, a freely available, IBSI-compliant tool, features its intuitive Graphical User Interface (GUI), facilitating the entire radiomics workflow from DICOM image importation to segmentation, feature selection and extraction, and Machine Learning model construction. In this project, an extension of matRadiomics was developed to support the importation of brain MRI images and segmentations in NIfTI format, thus extending its applicability to neuroimaging. This enhancement allows for the seamless execution of radiomic pipelines within matRadiomics, offering substantial advantages to the realm of neuroimaging.

Сведения

Название
Development and Implementation of an Innovative Framework for Automated Radiomics Analysis in Neuroimaging
Автор
Camastra, Chiara 1   Логотип VIAFID ORCID  ; Pasini, Giovanni 2   Логотип VIAFID ORCID  ; Stefano, Alessandro 3   Логотип VIAFID ORCID  ; Russo, Giorgio 3 ; Vescio, Basilio 4   Логотип VIAFID ORCID  ; Bini, Fabiano 1   Логотип VIAFID ORCID  ; Marinozzi, Franco 1 ; Augimeri, Antonio 5 

 Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Eudossiana 18, 00184 Rome, Italy; giovanni.pasini@uniroma1.it (G.P.); fabiano.bini@uniroma1.it (F.B.); franco.marinozzi@uniroma1.it (F.M.) 
 Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Eudossiana 18, 00184 Rome, Italy; giovanni.pasini@uniroma1.it (G.P.); fabiano.bini@uniroma1.it (F.B.); franco.marinozzi@uniroma1.it (F.M.); Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù and 88100 Catanzaro, Italy; alessandro.stefano@ibfm.cnr.it (A.S.); giorgio-russo@cnr.it (G.R.); or basilio.vescio@biotecnomed.it (B.V.) 
 Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù and 88100 Catanzaro, Italy; alessandro.stefano@ibfm.cnr.it (A.S.); giorgio-russo@cnr.it (G.R.); or basilio.vescio@biotecnomed.it (B.V.) 
 Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù and 88100 Catanzaro, Italy; alessandro.stefano@ibfm.cnr.it (A.S.); giorgio-russo@cnr.it (G.R.); or basilio.vescio@biotecnomed.it (B.V.); Biotecnomed SCARL, Campus Universitario di Germaneto, Viale Europa, 88100 Catanzaro, Italy; antonio.augimeri@biotecnomed.it 
 Biotecnomed SCARL, Campus Universitario di Germaneto, Viale Europa, 88100 Catanzaro, Italy; antonio.augimeri@biotecnomed.it 
Первая страница
96
Год публикации
2024
Дата публикации
2024
Издательство
MDPI AG
e-ISSN
2313433X
Тип источника
Научный журнал
Язык публикации
English
ИД документа ProQuest
3047001622
Авторское право
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.