CNN Based Segmentation of Infarcted Regions in Acute Cerebral Stroke Patients From Computed Tomography Perfusion Imaging. - Luca Tomasetti; Kjersti Engan; Mahdieh Khanmohammadi; Kathinka Dæhli Kurz (BCB, 2020)

Multi-input segmentation of damaged brain in acute ischemic stroke patients using slow fusion with skip connection. - Luca Tomasetti; Mahdieh Khanmohammadi; Kjersti Engan; Liv Jorunn Høllesli; Kathinka Dæhli Kurz (NLDL, 2022)

Machine Learning Algorithms Versus Thresholding to Segment Ischemic Regions in Patients With Acute Ischemic Stroke. - Luca Tomasetti; Liv Jorunn Høllesli; Kjersti Engan; Kathinka Dæhli Kurz; Martin Wilhelm Kurz; Mahdieh Khanmohammadi (IEEE J. Biomed. Health Informatics, 2022)

Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. - Luca Tomasetti; Stine Hansen; Mahdieh Khanmohammadi; Kjersti Engan; Liv Jorunn Høllesli; Kathinka Dæhli Kurz; Michael Kampffmeyer (ISBI, 2023)

CT Perfusion is All we Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Acute Ischemic Stroke. - Luca Tomasetti; Kjersti Engan; Liv Jorunn Høllesli; Kathinka Dæhli Kurz; Mahdieh Khanmohammadi (IEEE Access, 2023)

Exploiting 4D CT Perfusion for segmenting infarcted areas in patients with suspected acute ischemic stroke. - Luca Tomasetti; Kjersti Engan; Liv Jorunn Høllesli; Kathinka Dæhli Kurz; Mahdieh Khanmohammadi (CoRR, 2023)

Stroke Simulation: Generative AI for Computed Tomography Perfusion Synthesis. - Mahdieh Khanmohammadi; Luca Tomasetti; Ahmed A. Hassan; Ørjan Vier; Carl H. Christiansen; Kjersti Engan; Kathinka Dæhli Kurz (DSP, 2025)