Zobrazeno 1 - 10
of 319
pro vyhledávání: '"Leonardo Rundo a"'
Autor:
Leonardo Rundo, Carmelo Militello
Publikováno v:
European Radiology Experimental, Vol 8, Iss 1, Pp 1-13 (2024)
Abstract Feature extraction and selection from medical data are the basis of radiomics and image biomarker discovery for various architectures, including convolutional neural networks (CNNs). We herein describe the typical radiomics steps and the com
Externí odkaz:
https://doaj.org/article/1765c0d4ace146cca4d183cbbb953398
Autor:
Elizabeth P.V. Le, Mark Y.Z. Wong, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Jonathan R. Weir-McCall, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Fulvio Zaccagna, Chris Wall, Rouchelle Sriranjan, Andrej Corovic, Yuan Huang, Elizabeth A. Warburton, Evis Sala, Michael Roberts, Carola-Bibiane Schönlieb, James H.F. Rudd
Publikováno v:
European Journal of Radiology Open, Vol 13, Iss , Pp 100594- (2024)
Purpose: To assess radiomics and deep learning (DL) methods in identifying symptomatic Carotid Artery Disease (CAD) from carotid CT angiography (CTA) images. We further compare the performance of these novel methods to the conventional calcium score.
Externí odkaz:
https://doaj.org/article/5f3bf2f517c440329ea8eac866760768
Autor:
Cristiana Fiscone, Giovanni Sighinolfi, David Neil Manners, Lorenzo Motta, Greta Venturi, Ivan Panzera, Fulvio Zaccagna, Leonardo Rundo, Alessandra Lugaresi, Raffaele Lodi, Caterina Tonon, Mauro Castelli
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-11 (2024)
Abstract Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific le
Externí odkaz:
https://doaj.org/article/b715229596744fe69c4c6e3e5deca67f
Autor:
Thomas Buddenkotte, Leonardo Rundo, Ramona Woitek, Lorena Escudero Sanchez, Lucian Beer, Mireia Crispin-Ortuzar, Christian Etmann, Subhadip Mukherjee, Vlad Bura, Cathal McCague, Hilal Sahin, Roxana Pintican, Marta Zerunian, Iris Allajbeu, Naveena Singh, Anju Sahdev, Laura Havrilesky, David E. Cohn, Nicholas W. Bateman, Thomas P. Conrads, Kathleen M. Darcy, G. Larry Maxwell, John B. Freymann, Ozan Öktem, James D. Brenton, Evis Sala, Carola-Bibiane Schönlieb
Publikováno v:
European Radiology Experimental, Vol 7, Iss 1, Pp 1-10 (2023)
Abstract Purpose To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods. Methods A deep learning model for the two most common disea
Externí odkaz:
https://doaj.org/article/d86351df71064c6098a739ef36b913d9
Autor:
Mireia Crispin-Ortuzar, Ramona Woitek, Marika A. V. Reinius, Elizabeth Moore, Lucian Beer, Vlad Bura, Leonardo Rundo, Cathal McCague, Stephan Ursprung, Lorena Escudero Sanchez, Paula Martin-Gonzalez, Florent Mouliere, Dineika Chandrananda, James Morris, Teodora Goranova, Anna M. Piskorz, Naveena Singh, Anju Sahdev, Roxana Pintican, Marta Zerunian, Nitzan Rosenfeld, Helen Addley, Mercedes Jimenez-Linan, Florian Markowetz, Evis Sala, James D. Brenton
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-14 (2023)
Abstract High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherap
Externí odkaz:
https://doaj.org/article/f80cba9b3dae477aa79e30f52e6184bd
Autor:
Cristiana Fiscone, Leonardo Rundo, Alessandra Lugaresi, David Neil Manners, Kieren Allinson, Elisa Baldin, Gianfranco Vornetti, Raffaele Lodi, Caterina Tonon, Claudia Testa, Mauro Castelli, Fulvio Zaccagna
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging techniqu
Externí odkaz:
https://doaj.org/article/8a86b56aa3c341ffad9f0bc94b82e966
Autor:
Yuting Xie, Fulvio Zaccagna, Leonardo Rundo, Claudia Testa, Ruifeng Zhu, Caterina Tonon, Raffaele Lodi, David Neil Manners
Publikováno v:
Diagnostics, Vol 14, Iss 10, p 997 (2024)
Deep learning (DL) networks have shown attractive performance in medical image processing tasks such as brain tumor classification. However, they are often criticized as mysterious “black boxes”. The opaqueness of the model and the reasoning proc
Externí odkaz:
https://doaj.org/article/467d9f104c7b44268d275adad09b6778
Publikováno v:
Insights into Imaging, Vol 15, Iss 1, Pp 1-2 (2024)
Externí odkaz:
https://doaj.org/article/78a1da2db6d94ba78aaa807738e71b0b
Autor:
Lorena Escudero Sanchez, Emma Brown, Leonardo Rundo, Stephan Ursprung, Evis Sala, Sarah E. Bohndiek, Ignacio Xavier Partarrieu
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-4 (2022)
Externí odkaz:
https://doaj.org/article/226b357a3e304fcea002e1bd38f884fb
Autor:
Lorena Escudero Sanchez, Emma Brown, Leonardo Rundo, Stephan Ursprung, Evis Sala, Sarah E. Bohndiek, Ignacio Xavier Partarrieu
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Photoacoustic imaging is an increasingly popular method of exploring the tumour microenvironment, which can provide insight into tumour oxygenation status and potentially treatment response assessment. Currently, the measurements most common
Externí odkaz:
https://doaj.org/article/78bd63978b80444bb7690059d4de6b7e