フォロー
Tommaso Di Noto
Tommaso Di Noto
Siemens Healthineers
確認したメール アドレス: siemens-healthineers.com
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引用先
引用先
年
Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge
KM Timmins, IC van der Schaaf, E Bennink, YM Ruigrok, X An, ...
NeuroImage 238, 118216, 2021
692021
Radiomics for Distinguishing Myocardial Infarction from Myocarditis at Late Gadolinium Enhancement at MRI: Comparison with Subjective Visual Analysis
T Di Noto, J von Spiczak, M Mannil, E Gantert, P Soda, R Manka, ...
Radiology: Cardiothoracic Imaging 1 (5), e180026, 2019
382019
Towards automated brain aneurysm detection in TOF-MRA: open data, weak labels, and anatomical knowledge
T Di Noto, G Marie, S Tourbier, Y Alemán-Gómez, O Esteban, G Saliou, ...
Neuroinformatics - https://doi.org/10.1007/s12021-022-09597-0, 2022
322022
Machine learning algorithms on eye tracking trajectories to classify patients with spatial neglect
B Franceschiello, T Di Noto, A Bourgeois, MM Murray, A Minier, P Pouget, ...
Computer Methods and Programs in Biomedicine 221, 106929, 2022
122022
Diagnostic surveillance of high-grade gliomas: towards automated change detection using radiology report classification
TD Noto, C Atat, EG Teiga, M Hegi, A Hottinger, MB Cuadra, P Hagmann, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
52021
Amnestic Syndrome in Memory Clinics: Similar Morphological Brain Patterns in Older Adults with and without Alzheimer’s Disease
HM Lalive, A Griffa, S Carlier, M Nasuti, T Di Noto, B Maréchal, O Rouaud, ...
Journal of Alzheimer's Disease, 1-1, 2024
22024
An anatomically-informed 3D CNN for brain aneurysm classification with weak labels
T Di Noto, G Marie, S Tourbier, Y Alemán-Gómez, G Saliou, MB Cuadra, ...
Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro …, 2020
22020
Transfer learning with weak labels from radiology reports: application to glioma change detection
T Di Noto, MB Cuadra, C Atat, EG Teiga, M Hegi, A Hottinger, P Hagmann, ...
arXiv preprint arXiv:2210.09698, 2022
12022
Weak labels for deep-learning-based detection of brain aneurysms from MR angiography scans
T Di Noto, G Marie, S Tourbier, Y Alemán-Gómez, O Esteban, G Saliou, ...
Medical Imaging with Deep Learning, 2022
2022
Towards improving high-grade gliomas diagnostic surveillance on T2-weighted images using weak labels from radiology reports
T Di Noto, C Atat, EG Teiga, M Hegi, A Hottinger, P Hagmann, MB Cuadra, ...
2022
Improving automated aneurysm detection on multi-site MRA data: lessons learnt from a public machine learning challenge
T Di Noto, G Marie, S Tourbier, Y Alemán-Gómez, O Esteban, G Saliou, ...
2021
Artificial Intelligence and Radiomics: Outlook into the Future
T Di Noto, M Mannil, H Aerts, C Kadian
Neuroimaging Techniques in Clinical Practice, 335-342, 2020
2020
Establishing Magnetic Resonance Parkinsonism Index reference ranges to distinguish Progressive Supranuclear Palsy and Corticobasal Syndrome
T Di Noto, PB Venkategowda, R Corredor-Jerez, TR Bodenmann, ...
Automated Deep Learning-Based Magnetic Resonance Parkinsonism Index 2.0 in Early Parkinson’s Disease: A Longitudinal Study
S Hartono, PB Venkategowda, S Madappa, RC Jerez, B Maréchal, ...
CNN-based Automated Pipeline for Accurate Computation of Magnetic Resonance Parkinsonism’s Index Measurements
PB Venkategowda, T Di Noto, R Corredor-Jerez, T Bodenmann, ...
Towards clinical translation of single-subject characterization of T1 changes to capture the extent of focal tissue damage in multiple sclerosis
P Kuntke, C Köhler, L Hösel, GF Piredda, T Di Noto, S Caneschi, ...
Weakly Supervised Deep Learning Models for Anomaly and Change Detection in Radiology
T Di Noto
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論文 1–17