Melanie Ganz-Benjaminsen

Scientific interests:

My main research focus is on the application of image processing, computer vision and machine learning techniques in medical imaging as well as the statistical interpretations of results retrieved in medical imaging problems. During the last years, I have worked with high/dimensional regression on structural MRI images, especially focusing on the approach via sparse Bayesian learning, as well as the development of feature selection algorithms based on random forests. Currently, I am applying these types of algorithms to combined MR/PET data acquired at NRU.

Biography:

Publications:

For a full list, visit: https://sites.google.com/view/melanieganz/about-me/publications

Most recent work:

Ip CT, Ganz M, Ozenne B, Sluth LB, Gram M, Viardot G, l'Hostis P, Danjou P, Knudsen GM, Christensen SR. Pre-intervention test-retest reliability of EEG and ERP over four recording intervals. International Journal of Psychophysiology. 2018 Dec 1;134:30-43.

Carass A, Cuzzocreo JL, Han S, Hernandez-Castillo CR, Rasser PE, Ganz M, Beliveau V, Dolz J, Ayed IB, Desrosiers C, Thyreau B. Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images. NeuroImage. 2018 Dec 1;183:150-72.

Nørgaard M, Greve DN, Svarer C, Strother SC, Knudsen GM, Ganz M. The Impact of Preprocessing Pipeline Choice in Univariate and Multivariate Analyses of PET Data. In 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) 2018 June

Nørgaard M, Ganz M, Svarer C, Feng L, Ichise M, Lanzenberger R, Lubberink M, Parsey RV, Politis M, Rabiner EA, Slifstein M. Cerebral serotonin transporter measurements with [11C] DASB: A review on acquisition and preprocessing across 21 PET centres. Journal of Cerebral Blood Flow & Metabolism. 2018 Apr:0271678X18770107.

Nørgaard M, Ganz M, Svarer C, Fisher PM, Churchill NW, Beliveau V, Grady C, Strother SC, Knudsen GM. Brain networks implicated in seasonal affective disorder: a neuroimaging PET study of the serotonin transporter. Frontiers in neuroscience. 2017 Nov 3;11:614.

Ganz M, Feng L, Hansen HD, Beliveau V, Svarer C, Knudsen GM, Greve DN. Cerebellar heterogeneity and its impact on PET data quantification of 5-HT receptor radioligands. Journal of Cerebral Blood Flow & Metabolism. 2017 Sep;37(9):3243-52. http://journals.sagepub.com/doi/pdf/10.1177/0271678X16686092

Ganz M, Konukoglu E. Permutation tests for classification: revisited. In 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI) 2017 June

Beliveau V, Ganz M, Feng L, Ozenne B, Højgaard L, Fisher PM, Svarer C, Greve DN, Knudsen GM. A high-resolution in vivo atlas of the human brain's serotonin system. Journal of Neuroscience. 2017 Jan 4;37(1):120-8. http://www.jneurosci.org/content/early/2016/11/17/JNEUROSCI.2830-16.2016

Ganz M, Kondermann D, Andrulis J, Knudsen GM, Maier-Hein L. Crowdsourcing for error detection in cortical surface delineations. International journal of computer assisted radiology and surgery. 2017 Jan 1;12(1):161-6. http://link.springer.com/article/10.1007/s11548-016-1445-9 or http://rdcu.be/nxT2 (Received KUKA IJCARS Best Paper Award 3rd place)

Ettrup A, Svarer C, McMahon B, da Cunha-Bang S, Lehel S, Møller K, Dyssegaard A, Ganz M, Beliveau V, Jørgensen LM, Gillings N. Serotonin 2A receptor agonist binding in the human brain with [11C] Cimbi-36: Test–retest reproducibility and head-to-head comparison with the antagonist [18F] altanserin. Neuroimage. 2016 Apr 15;130:167-74. http://www.sciencedirect.com/science/article/pii/S1053811916000975

Ganz M, Greve DN, Fischl B, Konukoglu E, Alzheimer's Disease Neuroimaging Initiative. Relevant feature set estimation with a knock-out strategy and random forests. Neuroimage. 2015 Nov 15;122:131-48.

Konukoglu E, Ganz M. Approximate false positive rate control in selection frequency for random forest. arXiv preprint arXiv:1410.2838. 2014 Oct 10.