Information till studenter och medarbetare med anledning av covid-19 (Uppdaterad: 15 april 2021)

English
Umeå universitet
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Tufve Nyholm

PhD in Radiation Physics in 2009 and professor in 2018. The PhD thesis was focused on algorithms for dose calculations and quality assurance aspects on external radiotherapy. This work is partly the basis for the EqualDose software.

Currently, my main area of research is MRI in cancer care, including both integration of MR in the radiotherapy workflow and use of MR techniques for early assessment of treatment response.

Forskningsledare

Tufve Nyholm Professor, sjukhusfysiker
E-post
E-post
Telefon
090-786 72 92

Översikt

Medverkande institutioner och enheter vid Umeå universitet

Institutionen för strålningsvetenskaper

Forskningsområde

Medicinsk teknik
Bildgivande metoder för förbättrad strålbehandling
Bildgivande metoder för förbättrad strålbehandling

Tufve Nyholms forskning handlar om metod- och teknikutveckling inom strålterapi.

52 VR-miljoner till forskning inom naturvetenskap och teknik
52 VR-miljoner till forskning inom naturvetenskap och teknik

Vetenskapsrådet delar ut nära 52 miljoner till projekt inom naturvetenskap och teknikvetenskap.

Publikationer

Impact of neoadjuvant androgen deprivation therapy on magnetic resonance imaging features in prostate cancer before radiotherapy
Physics and Imaging in Radiation Oncology, Elsevier 2021, Vol. 17 : 117-123
Björeland, Ulrika; Nyholm, Tufve; Jonsson, Joakim; et al.
A Question-Centric Model for Visual Question Answering in Medical Imaging
IEEE Transactions on Medical Imaging, IEEE 2020, Vol. 39, (9) : 2856-2868
Vu, Minh Hoang; Löfstedt, Tommy; Nyholm, Tufve; et al.
Bayesian non-linear regression with spatial priors for noise reduction and error estimation in quantitative MRI with an application in T1 estimation
Physics in Medicine and Biology, Institute of Physics (IOP) 2020, Vol. 65, (22)
Löfstedt, Tommy; Hellström, Max; Bylund, Mikael; et al.
Dosimetric effects of adaptive prostate cancer radiotherapy in an MR-linac workflow
Radiation Oncology, BioMed Central 2020, Vol. 15, (1)
Mannerberg, Annika; Persson, Emilia; Jonsson, Joakim; et al.
Evaluation of multislice inputs to convolutional neural networks for medical image segmentation
Medical physics (Lancaster), John Wiley & Sons 2020, Vol. 47, (12) : 6216-6231
Vu, Minh H.; Grimbergen, Guus; Nyholm, Tufve; et al.
A constrained singular value decomposition method that integrates sparsity and orthogonality
PLoS ONE, Vol. 14, (3)
Guillemot, Vincent; Beaton, Derek; Gloaguen, Arnaud; et al.
Attenuation correction of a flat table top for radiation therapy in hybrid PET/MR using CT- and Ge-68/Ga-68 transmission scan-based mu-maps
Physica medica (Testo stampato), ELSEVIER SCI LTD 2019, Vol. 65 : 76-83
Witoszynskyj, Stephan; Andrzejewski, Piotr; Georg, Dietmar; et al.
Bayesian sparsity estimation in compressive sensing with application to MR images
Communications in Statistics: Case Studies, Data Analysis and Applications, Taylor & Francis Group 2019, Vol. 5, (4) : 415-431
Wang, Jianfeng; Zhou, Zhiyong; Garpebring, Anders; et al.
Dosimetric Impact of MRI Distortions: A Study on Head and Neck Cancers
International Journal of Radiation Oncology, Biology, Physics, Elsevier 2019, Vol. 103, (4) : 994-1003
Adjeiwaah, Mary; Bylund, Mikael; Lundman, Josef A.; et al.
Early changes in multiparametric imaging parameters during radiotherapy of squamous carcinoma
Radiotherapy and Oncology, Elsevier 2019, Vol. 132 : 63-63
Zborayova, Katarina; Antti, Henrik; Blomqvist, L.; et al.