Lineamentos da história do pensamento científico /

von Trebeschi, Alberto
Veröffentlicht 1977.

State-of-The-Art and Applications of 3D Imaging Sensors in Industry, Cultural Heritage, Medicine, and Criminal Investigation

von Sansoni, Giovanna, Trebeschi, Marco, Docchio, Franco
Veröffentlicht 2009

Radiomics: a critical step towards integrated healthcare

von Zuhir Bodalal, Stefano Trebeschi, Regina Beets-Tan
Veröffentlicht 2018-11-01

Radiomics: a critical step towards integrated healthcare

von Bodalal, Zuhir, Trebeschi, Stefano, Beets-Tan, Regina
Veröffentlicht in Insights Imaging (2018)

Modern MR Imaging Technology in Rectal Cancer; There Is More Than Meets the Eye

von Haak, Hester E., Maas, Monique, Trebeschi, Stefano, Beets-Tan, Regina G. H.
Veröffentlicht in Front Oncol (2020)

Opportunistic osteoporosis screening in multi-detector CT images via local classification of textures

von Valentinitsch, A., Trebeschi, S., Kaesmacher, J., Lorenz, C., Löffler, M. T., Zimmer, C., Baum, T., Kirschke, J. S.
Veröffentlicht in Osteoporos Int (2019)

Neurodevelopmental profile in Angelman syndrome: more than low intelligence quotient

von Micheletti, S., Palestra, F., Martelli, P., Accorsi, P., Galli, J., Giordano, L., Trebeschi, V., Fazzi, E.
Veröffentlicht in Ital J Pediatr (2016)

Diagnostic Potential of Pulsed Arterial Spin Labeling in Alzheimer's Disease

von Trebeschi, Stefano, Riederer, Isabelle, Preibisch, Christine, Bohn, Karl P., Förster, Stefan, Alexopoulos, Panagiotis, Zimmer, Claus, Kirschke, Jan S., Valentinitsch, Alexander
Veröffentlicht in Front Neurosci (2016)

Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas

von Eichinger, Paul, Alberts, Esther, Delbridge, Claire, Trebeschi, Stefano, Valentinitsch, Alexander, Bette, Stefanie, Huber, Thomas, Gempt, Jens, Meyer, Bernhard, Schlegel, Juergen, Zimmer, Claus, Kirschke, Jan S., Menze, Bjoern H., Wiestler, Benedikt
Veröffentlicht in Sci Rep (2017)

Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR

von Trebeschi, Stefano, van Griethuysen, Joost J. M., Lambregts, Doenja M. J., Lahaye, Max J., Parmar, Chintan, Bakers, Frans C. H., Peters, Nicky H. G. M., Beets-Tan, Regina G. H., Aerts, Hugo J. W. L.
Veröffentlicht in Sci Rep (2017)

Author Correction: Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR

von Trebeschi, Stefano, van Griethuysen, Joost J. M., Lambregts, Doenja M. J., Lahaye, Max J., Parmar, Chintan, Bakers, Frans C. H., Peters, Nicky H. G. M., Beets-Tan, Regina G. H., Aerts, Hugo J. W. L.
Veröffentlicht in Sci Rep (2018)

Development of a Prognostic AI-Monitor for Metastatic Urothelial Cancer Patients Receiving Immunotherapy

von Trebeschi, Stefano, Bodalal, Zuhir, van Dijk, Nick, Boellaard, Thierry N., Apfaltrer, Paul, Tareco Bucho, Teresa M., Nguyen-Kim, Thi Dan Linh, van der Heijden, Michiel S., Aerts, Hugo J. W. L., Beets-Tan, Regina G. H.
Veröffentlicht in Front Oncol (2021)

Prognostic Value of Deep Learning-Mediated Treatment Monitoring in Lung Cancer Patients Receiving Immunotherapy

von Trebeschi, Stefano, Bodalal, Zuhir, Boellaard, Thierry N., Tareco Bucho, Teresa M., Drago, Silvia G., Kurilova, Ieva, Calin-Vainak, Adriana M., Delli Pizzi, Andrea, Muller, Mirte, Hummelink, Karlijn, Hartemink, Koen J., Nguyen-Kim, Thi Dan Linh, Smit, Egbert F., Aerts, Hugo J. W. L., Beets-Tan, Regina G. H.
Veröffentlicht in Front Oncol (2021)

MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer

von Delli Pizzi, Andrea, Chiarelli, Antonio Maria, Chiacchiaretta, Piero, d’Annibale, Martina, Croce, Pierpaolo, Rosa, Consuelo, Mastrodicasa, Domenico, Trebeschi, Stefano, Lambregts, Doenja Marina Johanna, Caposiena, Daniele, Serafini, Francesco Lorenzo, Basilico, Raffaella, Cocco, Giulio, Di Sebastiano, Pierluigi, Cinalli, Sebastiano, Ferretti, Antonio, Wise, Richard Geoffrey, Genovesi, Domenico, Beets-Tan, Regina G. H., Caulo, Massimo
Veröffentlicht in Sci Rep (2021)

Predicting response to cancer immunotherapy using noninvasive radiomic biomarkers

von Trebeschi, S, Drago, S G, Birkbak, N J, Kurilova, I, Cǎlin, A M, Delli Pizzi, A, Lalezari, F, Lambregts, D M J, Rohaan, M W, Parmar, C, Rozeman, E A, Hartemink, K J, Swanton, C, Haanen, J B A G, Blank, C U, Smit, E F, Beets-Tan, R G H, Aerts, H J W L
Veröffentlicht in Ann Oncol (2019)