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Mahdieh Khanmohammadi

Førsteamanuensis

Faculty of Science and Technology

Department of Electrical Engineering and Computer Science
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Bio

Mahdieh Khanmohammadi works with basic research in medical signal/image processing, computer graphics, neural networks, and artificial intelligence. She is involved in several major, interdisciplinary research projects, for example: Image analysis and AI to investigate acute ischemic stroke (The project is in collaboration between University of Stavanger (UiS), Stavanger University Hospital (SUH)). Estimating coronary flow reserve using angiography imaging (A collaboration between University of Stavanger (UiS), Stavanger University Hospital (SUH), University of Copenhagen (KU)). She is a part of Cognitive and Behavioral Neuroscience Lab working on investigating the dementia progression in patients using EEG signals and functional magnetic resonance images. She is s part of CLoud ARtificial Intelligence For pathologY (CLARIFY), where the main goal of the project is to develop a digital diagnostic environment that facilitates whole-slide-image (WSI) interpretation and diagnosis everywhere. 

Presently, she is particularly interested in analyzing medical signals and images to provide new insight into diseases such as stroke, cancer, dementia and heart related ones and insights that poses a computer modeling challenge.

Mahdieh Khanmohammadi has been employed as associate professor at IDE since 2019. She received her Master and PhD degree from University of Halmstad and University of Copenhagen (DIKU) in 2012 and 2015, respectively. Her PhD program was carried out as a part of The Centre for Stochastic Geometry and Advance Bioimaging (CSGB). Following her PhD, she worked as a visiting researcher at the Department of Mathematics and Statistics, Aalborg University, Denmark. In 2016, she became a post doctorate fellow at IDE.

Courses:

Electrical engineering 1 (Elektroteknikk 1) ELE100; Bachelor level

Medical images and signals ELE670; Master level

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Publications
  • Vitenskapelige publikasjoner
    • Tomasetti, Luca; Engan, Kjersti; Khanmohammadi, Mahdieh; Kurz, Kathinka Dæhli

      (2020)

      CNN based segmentation of infarcted regions in acute cerebral stroke patients from computed tomography perfusion imaging. I: BCB 20 : 11th ACM international conference on iioinformatics computational biology and health informatics : Virtual event USA September, 2020.

      Association for Computing Machinery (ACM)

      ISBN 9781450379649.

      DOI: 10.1145/3388440.3412470

    • Khanmohammadi, Mahdieh; Engan, Kjersti; Sæland, Charlotte; Eftestøl, Trygve Christian; Larsen, Alf Inge

      (2019)

      Automatic estimation of coronary blood flow velocity step 1 for developing a tool to diagnose patients with micro-vascular angina pectoris.

      Frontiers in Cardiovascular Medicine

      ISSN 2297-055X.

      Volum 6:1.

      s.1-11.

      DOI: 10.3389/fcvm.2019.00001

    • Khanmohammadi, Mahdieh; Engan, Kjersti; Eftestøl, Trygve Christian; Sæland, Charlotte; Larsen, Alf Inge

      (2017)

      SEGMENTATION OF CORONARY ARTERIES FROM X-RAY ANGIOGRAPHY SEQUENCES DURING CONTRAST FLUID PROPAGATION BY IMAGE REGISTRATION. I: Proceedings Global Conferance on Signal and Information Processing GlobalSIP 2017.

      IEEE Signal Processing Society

      ISBN 978-1-5090-5990-4.

    • Coeurjolly, Jean-Francois; Guan, Yongtao; Khanmohammadi, Mahdieh; Waagepetersen, Rasmus

      (2016)

      Towards optimal Takacs–Fiksel estimation.

      Spatial Statistics

      ISSN 2211-6753.

      Volum 18.

      s.396-411.

      DOI: 10.1016/j.spasta.2016.08.002

  • Bøker og kapitler
  • Formidling
    • Tomasetti, Luca; Engan, Kjersti; Khanmohammadi, Mahdieh; Kurz, Kathinka Dæhli

      (2020)

      mJ-Net: CNN based segmentation of infarcted regions in ischemic cerebral stroke from CTP imaging.

    • Tomasetti, Luca; Engan, Kjersti; Khanmohammadi, Mahdieh; Kurz, Kathinka Dæhli

      (2020)

      Automatic segmentation of infarcted regions from computed tomography perfusion imaging using 3D Convolutional Neural Network.

    • Khanmohammadi, Mahdieh; Engan, Kjersti; Eftestøl, Trygve Christian; sæland, charlotte; Larsen, Alf Inge

      (2017)

      SEGMENTATION OF CORONARY ARTERIES FROM X-RAY ANGIOGRAPHY SEQUENCES DURING CONTRAST FLUID PROPAGATION BY IMAGE REGISTRATION.

  • Kunstnerisk produksjon
  • Kommersialisering
  • Cristin hovedlogo, Cristin current research information system in Norway