Turid Torheim

Breast cancer tumours show heterogeneity at all levels: as genomic variation, tissue heterogeneity and heterogeneous appearance in radiological images. Data at all these levels are available, but so far there have been no integrative studies where all levels of heterogeneity are combined to gain comprehensive understanding of the disease. My project aims to fill this major gap by describing, comparing and correlating breast cancer heterogeneity at multiple levels.


since 04/2016
Postdoctoral research at Cancer Research UK Cambridge Research Institute

02/2012 - 04/2016
PhD student at the Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Norway.
Main advisor: Prof. Cecilia Marie Futsaether


Ph.D in Computational Biology
Norwegian University of Life Sciences

M.Sc. in Mathematical, Physical and Computational Sciences
Norwegian University of Life Sciences

B.Sc. in Natural Sciences (Physics)
Norwegian University of Life Sciences

Turid Torheim

Turid Torheim
University of Cambridge
CRUK Cambridge Institute
Li Ka Shing Centre
Robinson Way
Cambridge, CB2 0RE, UK
e: first.last@cruk.cam.ac.uk
p: +44 (0) 1223 40 4318

CRUK logo Cambridge University


Turid Torheim, Aurora R Groendahl, Erlend K. F. Andersen, Knut Kvaal, Heidi Lyng, Eirik Malinen, Cecilia M. Futsaether.
Cluster analysis of dynamic contrast enhanced MRI reveals tumour subregions related to locoregional relapse for cervical cancer patients.
Acta Oncologica, in press. 2016.
PMID:27564398 | doi: 10.1080/0284186X.2016.1189091

Alexandr Kristian, Jon Erik Holtedahl, Turid Torheim, Cecilia Futsaether, Eivor Hernes, Olav Engebraaten, Gunhild Maelandsmo, Eirik Malinen.
Dynamic 2-deoxy-2- [18F]fluoro-d-glucose positron emission tomography for chemotherapy response monitoring of breast cancer xenografts.
Molecular Imaging and Biology, in press. 2016.
PMID:27541026 | doi:10.1007/s11307-016-0998-x

Turid Torheim, Eirik Malinen, Knut Kvaal, Heidi Lyng, Ulf G. Indahl, Erlend K. F. Andersen, Cecilia M. Futsaether.
Classification of dynamic contrast enhanced MR images of cervical cancer using texture analysis and support vector machines.
IEEE Transactions on Medical Imaging 33: 1648-1656. 2014.
PMID:24802069 | doi: 10.1109/TMI.2014.2321024