Mahdieh Khanmohammadi

Førsteamanuensis i elektroteknologi

Mahdieh Khanmohammadi

Kontakt

Telefon: 51832761

E-post: mahdieh.khanmohammadi@uis.no

Rom: KE E-427

Organisasjonsenhet

Det teknisk-naturvitenskapelige fakultet

Institutt for data- og elektroteknologi

Kort om meg

I am currently an Associate Professor in Signal Processing at the Department of Electrical Engineering and Computer Science, University of Stavanger (UiS), Norway. My research focuses on medical signal and image analysis, artificial intelligence, and medical data synthesization, with applications in understanding and diagnosing diseases such as stroke, cancer, Parkinson’s disease, and cardiovascular conditions.

I received my Master’s degree in 2012 from the University of Halmstad, Sweden and my Ph.D. in Computer Science in 2015 from the University of Copenhagen, where my doctoral research was part of The Centre for Stochastic Geometry and Advanced Bioimaging (CSGB). Following my Ph.D., I visited the Department of Mathematics and Statistics, Aalborg University, Denmark. Then I joined UiS as a postdoctoral fellow in 2016 at the department of Electrical Engineering and Computer Science. In 2019, I became Associate Professor in signal processing at UiS.

 

Teaching competences:

  • Introduction to university pedagogy (100 hours, university of Copenhagen, 2014)
  • Mentoring for and with new staff - Nyti (50 hours, UiS, 2021)
  • PhD-supervisory qualification program (100 hours, UiS, 2020)

Currently taught courses:

Electrical engineering (ELE100)

Medical Imaging with AI Integration (ELE670)

 

Dette forsker jeg på

I am involved in interdisciplinary research projects, including:

  • Image analysis and AI for acute ischemic stroke – in collaboration between UiS and Stavanger University Hospital (SUS).
  • Investigating neurodegenerative disease progression using multimodal multi-temporal data – as part of the Cognitive and Behavioral Neuroscience Lab and in collaboration with SUS.
  • Estimating coronary flow reserve using angiography imaging – a collaboration between UiS, and the University of Copenhagen.

My current research aims to develop advanced computational methods for extracting and synthesizing clinically meaningful information from medical data, addressing both fundamental scientific challenges and real-world healthcare needs.

 

Følg meg på nett

LinkedIn

Publikasjoner

Vitenskapelige publikasjoner

Khanmohammadi, Mahdieh; Zafar, Aziz; Eftestøl, Trygve Christian; Brønnick, Kolbjørn Kallesten

(2025)

Automatic Classification of Neurodegenerative Disorders Using EEG Data.

Frontiers of Artificial Intelligence, Ethics and Multidisciplinary Applications.

ISSN 2731-8125.

Tomasetti, Luca; Hansen, Stine; Khanmohammadi, Mahdieh; Engan, Kjersti; Høllesli, Liv Jorunn; Kurz, Kathinka Dæhli; Kampffmeyer, Michael Christian

(2023)

Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation.

IEEE International Symposium on Biomedical Imaging.

ISSN 1945-7928.

DOI: 10.1109/ISBI53787.2023.10230655

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

(2023)

CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Acute Ischemic Stroke.

IEEE Access.

ISSN 2169-3536.

Volum 11.

s.138936-138953.

DOI: 10.1109/ACCESS.2023.3336590

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.

Volum 3.

DOI: 10.7557/18.6223

Tomasetti, Luca; Høllesli, Liv Jorunn; Engan, Kjersti; Kurz, Kathinka Dæhli; Kurz, Friedrich Martin Wilhelm; Khanmohammadi, Mahdieh

(2021)

Machine learning algorithms vs. thresholding to segment ischemic regions in patients with acute ischemic stroke .

IEEE Journal of Biomedical and Health Informatics.

ISSN 2168-2194.

s.1-12.

DOI: 10.1109/JBHI.2021.3097591

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

Formidling

Khanmohammadi, Mahdieh; Eftestøl, Trygve Christian; Zafar, Aziz; Brønnick, Kolbjørn Kallesten

(2024)

Automatic Classification of Neurodegenerative Disorders Using EEG Data.

International Conference on Frontiers of Artificial Intelligence, Ethics, and Multidisciplinary Applications;

2024-10-01 - 2024-10-02.

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

(2024)

CT Perfusion Synthesis Using GANs and Vision Transformers.

NORA annual conference;

2024-06-03 - 2024-06-04.

Khanmohammadi, Mahdieh

(2024)

Application of signal/image processing to solve medical problems.

Applied Signal Processing Workshop: Joining academia and industry for better good!;

2024-11-12.

Høllesli , Liv Jorunn; Tomasetti, Luca; Mouridsen, Kim; Kurz, Martin; Engan, Kjersti; Khanmohammadi, Mahdieh; Fjetland, Lars; Kurz, Kathinka Dæhli

(2023)

In patients with large vessel occlusion acute ischemic stroke, the distribution of CTP capillary transit time heterogeneity voxel values differs in recanalized versus non-recanalized patients.

European Stroke Organisation Conference 2023;

2023-05-24 - 2023-05-26.

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 Temporal Convolution Network.

NORA Annual Conference 2022;

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

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; 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.