Jennifer Alvén

PhD, Electrical engineering

Jennifer Alvén is a PhD in the Computer Vision and Medical Image Analysis research group. Jennifer conducts research in the field of medical image, the focus is machine learning, as well as explicit and implicit shape models, for classification and segmentation of medical 2D and 3D images. Examples of current applications are pericardium segmentation (CTA), heart ultrasound classification and coronary artery segmentation and classification (CTA). See the 'Research' tab for more infomation regarding these projects.


Jennifer is a member of WiSE (
Former master thesis students:
  • Elin Björnsson & Jan Liu, M.Sc. 2020: Automatic assessment of cardiac ultrasound images using deep learning.
  • Daniel Hallberg & Oscar Nilsagård, M.Sc. 2019: Eye region segmentation using deep learning for Smart Eye tracking systems at Smart Eye.
  • Charlotta Aguirre Nilsson & Medina Velic, M.Sc. 2018: Classification of ulcer images using convolutional neural networks at QRTECH
  • Fredrik Ring, M.Sc. 2018: Deep Learning for coronary artery segmentation in CTA images.
  • Henrik Hallberg & Victor Wessberg, M.Sc. 2018: Detection of child-like objects inside vehicles using deep learning at Alten
  • Jenny Nilsson, M.Sc. 2017: Feature-based quality assessment for spoof fingerprint images at Fingerprint Cards.​
  • Elvin Alcevska, M.Sc. 2016: Segmentation of the left ventricle of the heart in 2D ultrasound images using convolutional neural networks.
  • Bolin Shao, M.Sc. 2016: Pericardium segmentation in non-contrast cardiac CT images using convolutional neural networks​.
SSY186 Diagnostic imaging - Teaching assistant (VT 2019)
SSY096 Image analysis - Teaching assistant (VT 2015-2019)
SSY130 Applied signal processing - Teaching assistant (HT 2016-2017)
​​EMI084 CIrcuit analysis - Teaching assistant (HT 2015)
Ongoing research projects: 
  • Coronary artery segmentation and stenosis detection and classification​ in CTA (in collaboration with SCAPIS)
  • Pericardium segmentation and epicardial fat volume estimation in CTA and CT (in collaboration with SCAPIS)
  • Classification of heart ultrasound images (in collaboration with Sahlgrenska Academy)​
WiSE (Women in SciencE): ​ A project with the intention to support and create networks for young female researchers.

​​MedTech West: A network and collaborative platform for research, education, development and evaluation of new biomedical concepts and technologies.

  • Awarded IBM best student paper (track: Biomedical image analysis and applications) at ICPR (International Conference on Pattern Recognition) 2016 for the paper Shape-aware multi-atlas segmentation.​​
  • Awarded Best student paper at SCIA (Scandinavian Conference on Image Analysis) 2015 for the paper Uberatlas: Robust speed-up of feature-based registration and multi-atlas segmentation.

Page manager Published: Mon 28 Sep 2020.