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Jennifer Alvén is an Assistant Professor specializing in the fields of Computer Vision and Medical Image Analysis at the University of Gothenburg. Her research focuses on the development of advanced analytical techniques and algorithms for interpreting medical imaging data, particularly in the context of echocardiography and computed tomography. Jennifer has contributed to significant publications in high-quality annotations using deep learning for plaque analysis in cardiac computed tomography angiography. She has also explored semi-supervised learning approaches for right ventricle classification. Her work includes the quantitative analysis of bone marrow fat fraction in older women utilizing high-resolution imaging technologies. Throughout her career, she has been involved in enhancing multi-atlas segmentation methods and improving robust registration techniques across diverse medical imaging applications. Jennifer remains actively engaged in research collaborations aimed at advancing the capabilities of diagnostic imaging in clinical practices.
Administered by the Department of Political Science; focus on International Administration and Global Governance (IAGG).