Umeå universitet
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Huvudmenyn dold.

Tufve Nyholm

Forskargrupp 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.

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.

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

Cancer, Medicinsk teknik
Bildgivande metoder för förbättrad strålbehandling

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

Nya Cancerfondsmiljoner till Umeå

Forskning vid Umeå universitet får totalt 21,7 miljoner kronor i Cancerfondens tilldelning hösten 2021.

VR-miljoner till forskning i naturvetenskap och teknik

Vetenskapsrådet delar ut drygt 72 miljoner kronor till forskningsprojekt inom naturvetenskap och teknik.

AI-projekt som förbättrar behandling av barncancer får tre miljoner

Med medel från Barncancerfonden ska datavetare Tommy Löfstedt automatisera strålbehandling inom barnonkologi.

Publikationer

An MR-only acquisition and artificial intelligence based image-processing protocol for photon and proton therapy using a low field MR
Zeitschrift für Medizinische Physik, Elsevier 2021, Vol. 31, (1) : 78-88
Zimmermann, Lukas; Buschmann, Martin; Herrmann, Harald; et al.
Artificial intelligence and the medical physics profession - A Swedish perspective
Physica medica (Testo stampato), Elsevier 2021, Vol. 88 : 218-225
Andersson, Jonas; Nyholm, Tufve; Ceberg, Crister; et al.
Assessing cerebral arterial pulse wave velocity using 4D flow MRI
Journal of Cerebral Blood Flow and Metabolism
Björnfot, Cecilia; Garpebring, Anders; Qvarlander, Sara; et al.
Contrast Agent Quantification by Using Spatial Information in Dynamic Contrast Enhanced MRI
Frontiers in Signal Processing, Frontiers Media S.A. 2021, Vol. 1
Wang, Jianfeng; Garpebring, Anders; Brynolfsson, Patrik; et al.
Deep learning-based classification and structure name standardization for organ at risk and target delineations in prostate cancer radiotherapy
Journal of Applied Clinical Medical Physics
Jamtheim Gustafsson, Christian; Lempart, Michael; Swärd, Johan; et al.
Estimation of patient skin dose in fluoroscopy: summary of a joint report by AAPM TG357 and EFOMP
Medical physics (Lancaster)
Andersson, Jonas; Bednarek, Daniel R.; Bolch, Wesley; et al.
ESTRO ACROP guideline for target volume delineation of skull base tumors
Radiotherapy and Oncology, Elsevier 2021, Vol. 156 : 80-94
Combs, Stephanie E.; Baumert, Brigitta G.; Bendszus, Martin; 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.
Nya Cancerfondsmiljoner till Umeå

Forskning vid Umeå universitet får totalt 21,7 miljoner kronor i Cancerfondens tilldelning hösten 2021.