Jennifer Alvén

PhD Student, Electrical engineering

Jennifer Alvén is a PhD student in the Computer Vision and Medical Image Analysis research group. Jennifer conducts research in the field of medical image analysis with Fredrik Kahl and Olof Enqvist as supervisors. Her research 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 PET image registration, pericardium segmentation, heart ultrasound classification and coronary artery segmentation and classification. See the 'Research' tab for more infomation regarding these projects.

Jennifers has been interviewed by forskning.se (Swedish only):
https://www.forskning.se/2018/05/02/algoritmen-varnar-innan-hjartinfarkten-ar-ett-faktum/

Jennifer has blogged for Chalmers (Swedish only): http://www.chalmers.se/sv/forskning/chalmersforskning/artificiell-lakarlicens/Sidor/default.aspx

Jennifer is a project leader for WiSE (chalmers.se/wise) and is a member of the E2 PhD council.
Former master thesis students:
  • 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​.
Courses:
​​SSY096 Image analysis - Teaching assistant (VT 2015-2018)
SSY130 Applied signal processing - Teaching assistant (HT 2016-2017)
​​EMI084 CIrcuit analysis - Teaching assistant (HT 2015)
Ongoing research projects: 
  • ​Image registration of Tau PET images​ (in collaboration with Schöll group)
  • 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.

Published: Fri 20 Mar 2015. Modified: Fri 14 Sep 2018