Blar i NTNU Open på forfatter "Sunoqrot, Mohammed R. S."

Viser treff 1-9 av 9

    • Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges 

      Sunoqrot, Mohammed R. S.; Saha, Anindo; Hosseinzadeh, Matin; Elschot, Mattijs; Huisman, Henkjan J (Peer reviewed; Journal article, 2022)
      Artificial intelligence (AI) for prostate magnetic resonance imaging (MRI) is starting to play a clinical role for prostate cancer (PCa) patients. AI-assisted reading is feasible, allowing workflow reduction. A total of ...

    • Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges 

      Sunoqrot, Mohammed R. S.; Saha, Anindo; Hosseinzadeh, Matin; Elschot, Mattijs; Huisman, Henkjan J (Peer reviewed; Journal article, 2022)
      Artificial intelligence (AI) for prostate magnetic resonance imaging (MRI) is starting to play a clinical role for prostate cancer (PCa) patients. AI-assisted reading is feasible, allowing workflow reduction. A total of ...

    • Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition 

      Sunoqrot, Mohammed R. S.; Nketiah, Gabriel Addio; Selnæs, Kirsten Margrete; Bathen, Tone Frost; Elschot, Mattijs (Peer reviewed; Journal article, 2020)
      Objectives To develop and evaluate an automated method for prostate T2-weighted (T2W) image normalization using dual-reference (fat and muscle) tissue. Materials and methods Transverse T2W images from the publicly ...

    • A comparison of Generative Adversarial Networks for automated prostate cancer detection on T2-weighted MRI 

      Patsanis, Alexandros; Sunoqrot, Mohammed R. S.; Langørgen, Sverre; Wang, Hao; Selnæs, Kirsten Margrete; Bertilsson, Maria Helena; Bathen, Tone Frost; Elschot, Mattijs (Journal article; Peer reviewed, 2023)
      Generative Adversarial Networks (GANs) have shown potential in medical imaging. In this study, several previously developed GANs were investigated for prostate cancer (PCa) detection on T2-weighted (T2W) magnetic resonance ...

    • CROPro: a tool for automated cropping of prostate magnetic resonance images 

      Patsanis, Alexandros; Sunoqrot, Mohammed R. S.; Bathen, Tone Frost; Elschot, Mattijs (Peer reviewed; Journal article, 2023)
      Purpose To bypass manual data preprocessing and optimize deep learning performance, we developed and evaluated CROPro, a tool to standardize automated cropping of prostate magnetic resonance (MR) images. Approach CROPro ...

    • Label-set impact on deep learning-based prostate segmentation on MRI 

      Meglic, Jakob; Sunoqrot, Mohammed R. S.; Bathen, Tone Frost; Elschot, Mattijs (Peer reviewed; Journal article, 2023)
      Background Prostate segmentation is an essential step in computer-aided detection and diagnosis systems for prostate cancer. Deep learning (DL)-based methods provide good performance for prostate gland and zones ...

    • Pseudo-T2 mapping for normalization of T2-weighted prostate MRI 

      Sørland, Kaia Ingerdatter; Sunoqrot, Mohammed R. S.; Sandsmark, Elise; Langørgen, Sverre; Bertilsson, Helena; Trimble, Christopher George; Lin, Gigin; Selnæs, Kirsten Margrete; Goa, Pål Erik; Bathen, Tone Frost; Elschot, Mattijs (Peer reviewed; Journal article, 2022)
      Objective Signal intensity normalization is necessary to reduce heterogeneity in T2-weighted (T2W) magnetic resonance imaging (MRI) for quantitative analysis of multicenter data. AutoRef is an automated dual-reference ...

    • A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI 

      Sunoqrot, Mohammed R. S.; Selnæs, Kirsten Margrete; Sandsmark, Elise; Nketiah, Gabriel Addio; Zavala-Romero, Olmo; Stoyanova, Radka; Bathen, Tone Frost; Elschot, Mattijs (Journal article; Peer reviewed, 2020)
      Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of magnetic resonance imaging (MRI). Fully automated segmentation ...

    • The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images 

      Sunoqrot, Mohammed R. S.; Selnæs, Kirsten Margrete; Sandsmark, Elise; Langørgen, Sverre; Bertilsson, Helena; Bathen, Tone Frost; Elschot, Mattijs (Peer reviewed; Journal article, 2021)
      Volume of interest segmentation is an essential step in computer-aided detection and diagnosis (CAD) systems. Deep learning (DL)-based methods provide good performance for prostate segmentation, but little is known about ...