Jennifer Alvén

Postdoctoral researcher, Electrical engineering

Jennifer Alvén is a postdoctoral researcher affiliated with the Computer Vision research group. Jennifer pursues research in the field of medical image analysis, and the focus is deep machine learning for medical image understanding and analysis. Examples of current applications are automatic echocardiography (cardiac ultrasound) analysis, and detection, segmentation and classification of plaques and stenoses in corornary CTA.
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​.
Courses:
SSY186 Diagnostic imaging - Resonsible teacher (VT 2021), teaching assistant (VT 2019)
SSY096 Image analysis - Guest lecturing (VT 2017-2022), teaching assistant (VT 2015-2019)
SSY130 Applied signal processing - Teaching assistant (HT 2016-2017)
​​EMI084 CIrcuit analysis - Teaching assistant (HT 2015)
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  • Granted Vinnova project Scapis AI-plattform (4.2 MSEK) 2020-2022.
  • Awarded Best Swedish thesis 2019-2020 by Swedish Society for Automated Image Analysis.
  • 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 31 Jan 2022.