Calastra, Camilla Giulia

Up a level
Export as [feed] RSS
Group by: Date | Item Type | Refereed | No Grouping

Calastra, Camilla Giulia; Haupt, Fabian; Kleban, Elena; Huber, Adrian; Becker, Daniel; von Tengg-Kobligk, Hendrik; Jung, Bernd (June 2023). Contrast-enhanced MRA with GRASP outperforms the conventional TWIST in aortic dissection patient cohort (Unpublished). In: ISMRM 2023.

Sutter, Aurèle Dionys; Wegmüller, J; Tuleja, A; Huber, Adrian Thomas; Calastra, Camilla Giulia; Rössler, J; Döring, Yvonne; Baumgartner, Iris; von Tengg-Kobligk, Hendrik; Haupt, Fabian (June 2023). 3D segmentation and ruler-based volumetry of extra-cranial venous malformations in MRI with MRA (Unpublished). In: Swiss Congress of Radiology, SCR'23. Davos, Switzerland. June 2023.

Calastra, Camilla Giulia; Haupt, Fabian; Kleban, Elena; Huber, Adrian Thomas; von Tengg-Kobligk, Hendrik; Jung, Bernd (March 2023). Contrast-enhanced MRA with GRASP outperforms the conventional TWIST in aortic dissection patients cohort (Unpublished). In: European Congress of Radiology (ECR). Vienna.

Haupt, Fabian; Huber, Adrian Thomas; Calastra, Camilla Giulia; Tuleja, Aleksandra Beata; Rössler, Jochen Karl; Baumgartner, Iris; von Tengg-Kobligk, Hendrik (July 2022). Evaluation of MR biomarkers for advanced classification and therapy monitoring of patients with venous malformation (In Press). In: ECR 2022.

Haupt, Fabian; Huber, Adrian Thomas; Calastra, Camilla Giulia; Tuleja, Aleksandra Beata; Rössler, Jochen Karl; Baumgartner, Iris; von Tengg-Kobligk, Hendrik (June 2022). Magnet resonance imaging of congenital vascular malformations (Unpublished). In: SCR'22.

Bosbach, Wolfram Andreas; Senge, Jan Felix; Gurnari, Davide; Vergani, L; Buccino, Federica; Tindall, Marcus; Burfitt, Matthew; Stagg, Charlotte; Clarke, William; Heinrich, Martin; Kolisch, Rainer; Heiss, Christian; Ramedani, Saeid; von Tengg-Kobligk, Hendrik; Morhard, Christoph; Daneshvar, Keivan; Maryanski, M; Marszewska, M; Winiecki, Janusz; Haupt, Fabian; ... (April 2022). Automated Evaluation of the Whole Body's Muscle-fat Composition by Machine Learning for Magnetic Resonance Images (MRI). In: The 4th event of the Giessen International Conference Series on Trauma Surgery Technology. Warsaw. 10.5281/zenodo.7191419

Provide Feedback