Browsing NTNU Open by Author "Naseem, Rabia"

Now showing items 1-7 of 7

    • Cross modality guided liver image enhancement of CT using MRI 

      Naseem, Rabia; Alaya Cheikh, Faouzi; Beghdadi, Azeddine; Elle, Ole Jakob; Lindseth, Frank (Peer reviewed; Journal article, 2019)
      Low contrast Computed Tomographic (CT) images often hamper the diagnosis of critical tumors found in various human organs. Contrast enhancement schemes play significant role in improving the visualization of these structures. ...

    • Cross-modal guidance assisted hierarchical learning based siamese network for mr image denoising 

      Naseem, Rabia; Alaya Cheikh, Faouzi; Beghdadi, Azeddine; Muhammad, Khan; Sajjad, Muhammad (Journal article; Peer reviewed, 2021)

    • Cross-Modality Guided Contrast Enhancement for Improved Liver Tumor Image Segmentation 

      Naseem, Rabia; Khan, Zohaib Amjad; Satpute, Nitin; Beghdadi, Azeddine; Alaya Cheikh, Faouzi; Olivares, Joaquin (Journal article; Peer reviewed, 2021)

    • Cross-modality guided Image Enhancement 

      Naseem, Rabia (Doctoral theses at NTNU;2021:415, Doctoral thesis, 2021)
      The quality of medical images is a crucial factor that affects the performance of several image analysis tasks. Low contrast and noise are among the widely investigated distortions in medical image enhancement problems. ...

    • Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions 

      Survarachakan, Shanmugapriya; Prasad, Pravda Jith Ray; Naseem, Rabia; Perez de Frutos, Javier; Kumar, Rahul Prasanna; Langø, Thomas; Alaya Cheikh, Faouzi; Elle, Ole Jakob; Lindseth, Frank (Peer reviewed; Journal article, 2022)
      Deep learning-based methods, in particular, convolutional neural networks and fully convolutional networks are now widely used in the medical image analysis domain. The scope of this review focuses on the analysis using ...

    • GPU acceleration of liver enhancement for tumor segmentation 

      Naseem, Rabia; Cheikh, Faouzi Alaya (Peer reviewed; Journal article, 2019)
      Background and objective: Medical image segmentation plays a vital role in medical image analysis. There are many algorithms developed for medical image segmentation which are based on edge or region characteristics. These ...

    • Semi-supervised Network for Detection of COVID-19 in Chest CT Scans 

      Mohammed, Ahmed Kedir; Wang, Congcong; Zhao, Meng; Ullah, Mohib; Naseem, Rabia; Wang, Hao; Pedersen, Marius; Alaya Cheikh, Faouzi (Peer reviewed; Journal article, 2020)
      Deep Learning-based chest Computed Tomography (CT) analysis has been proven to be effective and efficient for COVID-19 diagnosis. Existing deep learning approaches heavily rely on large labeled data sets, which are difficult ...