Teaching & Supervision

Courses

Upcoming:

Spring 2025:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen  (course responsible).

Fall 2024:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen  (course responsible).

Ongoing/Finished:

Spring 2024:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen  (course responsible).

2024:

• Quantitative Reproducible Data Science, specialized PhD course at the Department for Computer Science of the University of Copenhagen in collaboration with Cyril Pernet.

Fall 2023:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen  (course responsible).

Spring 2023:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen together with Kenny Erleben.

2023:

• Quantitative Reproducible Data Science, specialized PhD course at the Department for Computer Science of the University of Copenhagen in collaboration with Cyril Pernet.

Fall 2022:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen  (course responsible).

Spring 2022:

• Data analysis and machine learnig for secondary school teachers in the Masteruddannelsen i informatikundervisning (Danish national MSc program)

• Professional module "Automatiseret billedeannalyse" in the Digital health and Data continuing education (in Danish only) 

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen together with Kenny Erleben.

Fall 2021:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen  (course responsible).

Spring 2021:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen together with Kenny Erleben.

Fall 2020:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen (course responsible).

Spring 2020:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen together with Kenny Erleben.

Fall 2019:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen together with Sune Darkner.

Spring 2019:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen together with Kenny Erleben.

Fall 2018:

No teaching due to maternity leave

Spring 2018:

• Computational Methods in Simulation (CMIS) at the Department for Computer Science of the University of Copenhagen together with Kenny Erleben.

Fall 2017:

• Medical Image Analysis at the Department for Computer Science of the University of Copenhagen together with Sune Darkner.

• Health care Technology at the Department for Computer Science of the University of Copenhagen and Denmarks Technical University together with Rasmus R. Paulsen.

Supervision

I am supervising Bachelor and Master projects. Please contact me if you are interested.

Previous/current students

PostDoc supervision (Danish/English)

• Vincent Beliveau, BrainDrugs WP5, 2021-2025 , NRU, Rigshospitalet.

• Eike Petersen, Bias and fairness in medicine, 2021-2023, DTU &  NRU, Rigshospitalet.

• Sreejita Ghosh,  Bias and fairness in medicine, 2021, DTU &  NRU, Rigshospitalet.

• Martin Nørgaard, OpenNeuroPET, 2019-2020, NRU, Rigshospitalet.

• Vincent Beliveau, NRU atlas project, 2018-2019, NRU, Rigshospitalet.

PhD student co-supervision (Danish/English) (see https://nru.dk/index.php/phd-projects) 

• Ruben Dörfel, "Developing and evaluating new and existing models for brain-age prediction", PhD thesis project, 2023-2027, Karolinska Institutet.

• Giske Opheim, “Severe epilepsy - a new era in the presurgical evaluation by ultra high field MR at 7 Tesla”, PhD thesis project, 2017-2020, KU SUND.

• Martin Nørgaard, “Optimizing Preprocessing Pipelines in PET/MRI Neuroimaging”, PhD thesis project, 2016-2019, KU SUND.

• Vincent Beliveau, “Brain connectivity of the serotonergic system”, PhD thesis project, 2015-2017, KU SUND.

Bachelor, Master and Skolarstipendie students (Danish/English) 

• Emma Cathrine Liisborg Leschly, "Toward Interpretable Multimodal Deep Learning for Neurological Assessment", Master thesis project, spring 2024, DIKU in collaboration with modality.ai.

• Jakob Sheye and Hvristo Georgiev, "Generative Models for Children’s Head Motion in Resting State Functional Magnetic Resonance Imaging", Master thesis project, spring 2024, DIKU.

• Mads Daugaard and Emil Christoffer Riis-Jacobsen, "Simulating Human Movement in MRI: A soft Phantom Head Approach with Machine Learning Integration",  Master thesis project, spring 2024, DIKU.

• Jakob Sheye, "Head movement in the tasked-based functional magnetic resonance imaging (fMRI) data of the ABCD study", Master student project, fall 2023, DIKU.

• Hvristo Georgiev, "Head movement in the diffusion and resting-state functional magnetic resonance imaging (fMRI) data of the ABCD study", Master student project, fall 2023, DIKU.

• Kyara Rozmann, "Development of an analysis pipeline for the automatic behavioural assessment and classification of rat models of neurodevelopmental", Master thesis project, fall 2023, DIKU.

• Kathrine Søndergaard Christensen, "MR-scanning af børn uden brug af bedøvelse eller general anæstesi", Master thesis project, spring 2023, KU SUND.

• Jingyu Huang, "Contrast-agnostic segmentation of deep brain nuclei in magnetic resonance images", Master thesis project, spring 2023, DIKU.

• Yaron Lahav and Jacob Lund, "EEG and PET based brain connectivity analysis for serotonin receptor concentration",  Bachelor thesis project, spring 2023, DIKU.

• Cheng Chen and Alexander Rubner Andersen, "Myelin in MDD", Master student project, spring 2023, DIKU and KU Math.

• Hector Lorenzo Mebenga Nnana, "Multiverse EEG study", Master student project, spring 2023, KU Math.

• Maude Plucker, "Automated classification of pharmaceutical fluid particles captured by Micro-Flow Imaging using machine learning", Master thesis project, spring 2022, DIKU in collaboration with Novo Nordisk.

• Kasper Meincke Iversen and Rikke Tophøj Heinemann,"Failure modes of concept layer-based approaches to explainable deep learning", Bachelor thesis project, spring 2022, DIKU.

• Avneet Kaur, "Development of a robust and reproducible preprocessing piepline for Positron Emission Tomography (PET) data", Master thesis project, fall 2021, DIKU.

• Alaa Al-Awadi, Cansu Gürel, Hanadi Hamza, "Forberedelse af børn til MR-scanning med App’en “Kom med i scanneren”, Bachelor thesis project, fall 2021, KP Metropol.

• Evangelos Vouros, " Reducing the Need for General Anesthesia in Children Undergoing Neuroimaging by Preparation and Motion Correction", Master thesis project, fall  2021/spring 2022, NBI.

• Simon Malik Chemnitz -Thomsen, " Reducing the Need for General Anesthesia in Children Undergoing Neuroimaging by Preparation and Motion Correction", Master thesis project, fall 2021, DIKU.

• Ramlah Sara Larsen, "Identification of typical shapes of trajectories in cortisol measurements", Bachelor thesis project, spring/summer 2021, DIKU.

• Bianca Ida Pedersen and Martin Riis Rassing, “Billedkvalitetsvurdering af prospektiv bevægelseskorrektion ved MR-skanninger af cerebrum”,  Bachelor thesis project, spring 2021, KP Metropol.

• Camilla Kergel Pedersen , "Demographic bias in public neuroimaging databases, and its effect on AI systems for computer-aided diagnosis", Master thesis project, spring 2021, DIKU.

• Liis Kivistik , "Evaluating task- and resting-state functional connectivity differences in major depressive disorder and prediction of antidepressant treatment response", Master thesis project, spring 2021, DIKU.

• Maria Luise da Costa Zemsch, "Uncovering bias in large and public datasets for medical image analysis", External master thesis project, spring/summer 2021, FAU Erlangen. 

• Hannah Eichhorn,"Comparison of prospective and retrospective motion correction for Magnetic Resonance Imaging", Master thesis project, Fall/winter 2020, NBI KU.

• Marc Fuglsang Christensen, "Gamificering af tålmodighed til MRI scanninger med VR teknologi", Master thesis project, spring 2020, DTU.

• Anders Lykkebo-Valløe, "Novel brain-states during psilocybin intervention", Master thesis project, spring 2020, DIKU.

• Ella Hedebø, "Evaluating subcortical volumetric differences in major depressive disorder", Bachelor thesis project, spring 2020, KU SUND.

• Emil Rasmussen, "Working on the cutting edge of neuroimaging - extending the BIDS validator to positron emission tomography (PET)", Bachelor thesis project, spring 2020, DIKU.

• Marcus Astrup Hansen,"Text Mining and Processing on Patients Experiences on Psilocybin", Bachelor thesis project, spring 2020, DIKU.

• Andreea-Veronica Vascan, "How do children move in the MR scanner with and without anaesthesia?", Master thesis project, winter 2019, DIKU.

• Michael Kha Dang Nguyen, "Visual tracking of rodent behaviour using deep learning", Master thesis project, fall 2019, DIKU.

• Kristine Nielsen, "Evaluating measures of intracranial volume in same subject multiple MR images over time", Master thesis project, spring 2019, DIKU.

• Emily Barot, "Optimization of Voxelwise and SurfaceBased Preprocessing Pipelines for PET Data", Master thesis project, spring 2019, DIKU.

• Maud Eline Ottenheijm, "Electric field modelling of TMS to predict BOLD measurements: a TMS-fMRI analysis", Master thesis project, spring 2019, DIKU.

• Kristine Aavild Juhl, ” Automated analysis of facial features from MR scannings”, Master thesis project, spring 2018, DTU.

• Christian Kildebro and Morten Tøstesen, “Manuel annotering af FCD på MR”, Bachelor thesis project in radiography, spring 2018, Professionshøjskole Metropol.

• Thomas Henrik Kawiecki, ”Analysis of network connectivity in subjects with Seasonal Affective Disorder using graph theory”, Bachelor thesis project, spring 2018, DIKU.

• Alexander Borch Christensen, “Does a brain parcellation based on 5-HT markers improve the detection of changes or differences in the 5-HT system?”, Bachelor thesis project, spring 2018, DTU.

• Mark Uhrskov Juul, “Evaluating changes in same-subject multiple MR images over time”, Master thesis project, spring 2017, DTU.

• Ditte Bentsen Christensen, „ Estimate short-term reproducibility of threat-related brain function assessed with fMRI “, Bachelor thesis project, spring 2017, DTU.

• Mathias Kølvraa, “Do human annotations on MRI data pay off? A statistical comparison of two manually annotated and two automatically computed surfaces”, research project, 2016, KU SUND.

• Martin Nørgaard, “Multivariate Estimation of Regional Seasonal Variations in SERT-levels in Seasonal Affective Disorder”, Master thesis project, spring 2015, DTU.

• Emil Jakob Holm, “Automatisk detektion af strukturelle forandringer hos raske mennesker og patienter opereret for epilepsi i perioden 2011-2014”, Skolarstiependie projekt, 2015, KU SUND.

• Casper Petersen, “Automation of measurements of pH levels in cancer cells”, Master student project April 2010, DIKU 

• Casper Petersen, “Automatic Rim Removal On X-Ray Images”, Master student project June 2010, DIKU