Mahdieh Khanmohammadi

Førsteamanuensis i elektroteknologi

Det teknisk-naturvitenskapelige fakultet
Institutt for data- og elektroteknologi
KE E-427
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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

Publikasjoner
  • Vitenskapelige publikasjoner
  • Bøker og kapitler
  • Formidling
    • Høllesli, Liv Jorunn; Tomasetti, Luca; Khanmohammadi, Mahdieh; Engan, Kjersti; Schulz, Jörn; Kurz, Friedrich Martin Wilhelm; Kurz, Kathinka Dæhli

      (2022)

      Kombinasjon av de parametriske CT perfusjonskartene TTP og CoV i pasienter med akutt ischemisk hjerneslag uten storkarsokklusjon predikerer penumbra. .

      Radiologisk høstmøte 2022;

      2022-10-26 - 2022-10-28.

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

      (2022)

      Predictions of infarcted areas in acute ischemic stroke using 4D TCN.

      hAIst Conference ;

      2022-06-13 - 2022-06-14.

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

      (2022)

      Multi-input segmentation of damaged brain in acute ischemic stroke patients using slow fusion with skip connection.

      Proceedings of the Northern Lights Deep Learning Workshop;

      2022-01-10 - 2022-01-12.

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

      (2022)

      Predictions of infarcted areas in acute ischemic stroke using 4D Temporal Convolution Network.

      NORA Annual Conference 2022;

      2022-06-09 - 2022-06-10.

    • 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.

      Northern Lights Deep Learning Workshop 2020;

      2020-01-19 - 2020-01-21.

    • 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.

      9th International Conference on Neurological Disorders and Stroke;

      2020-02-28 - 2020-02-29.

    • 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.

      IEEE Signal Processing ;

      2017-11-14 - 2017-11-16.

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