• A novel method for planning liver resections using deformable Bezier surfaces and distance maps 

      Palomar, Rafael; Alaya Cheikh, Faouzi; Edwin, Bjørn; Fretland, Åsmund Avdem; Beghdadi, Azeddine; Elle, Ole Jakob (Journal article; Peer reviewed, 2017)
      Background and Objective: For more than a decade, computer-assisted surgical systems have been helping surgeons to plan liver resections. The most widespread strategies to plan liver resections are: drawing traces in ...
    • Adaptive context encoding module for semantic segmentation 

      Wang, Congcong; Alaya Cheikh, Faouzi; Beghdadi, Azeddine; Elle, Ole Jacob (Peer reviewed; Journal article, 2020)
      The object sizes in images are diverse, therefore, capturing multiple scale context information is essential for semantic segmentation. Existing context aggregation methods such as pyramid pooling module (PPM) and atrous ...
    • Can Image Enhancement be Beneficial to Find Smoke Images in Laparoscopic Surgery? 

      Wang, Congcong; Sharma, Vivek; Fan, Yu; Alaya Cheikh, Faouzi; Beghdadi, Azeddine; Elle, Ole Jacob; Stiefelhagen, Rainer (Journal article; Peer reviewed, 2018)
      Laparoscopic surgery has a limited field of view. Laser ablation in a laproscopic surgery causes smoke, which inevitably influences the surgeon's visibility. Therefore, it is of vital importance to remove the smoke, such ...
    • Comparing the Chromatic Contrast Sensitivity in Vertical and Oblique Orientations 

      Amirshahi, Seyed Ali; Pedersen, Marius; Beghdadi, Azeddine (Journal article; Peer reviewed, 2019)
      While for many years achromatic contrast sensitivity has been widely studied by different research groups from various fields of work, the same attention has not been paid to chromatic contrast sensitivity. Due to the ...
    • A Critical Analysis on Perceptual Contrast and its Use in Visual Information Analysis and Processing 

      Beghdadi, Azeddine; Qureshi, Muhammad Ali; Amirshahi, Seyed Ali; Chetouani, Aladine; Pedersen, Marius (Peer reviewed; Journal article, 2020)
      Contrast in visible images is one of the most relevant characteristics of visual signals. Since the pioneering works performed in vision psychology and optics, different definitions have been proposed in the literature. ...
    • 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-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. ...
    • Efficient enhancement of stereo endoscopic images based on joint wavelet decomposition and binocular combination 

      Sdiri, Bilel; Kaaniche, Mounir; Alaya Cheikh, Faouzi; Beghdadi, Azeddine; Elle, Ole Jacob (Peer reviewed; Journal article, 2019)
      The success of minimally invasive interventions and the remarkable technological and medical progress have made endoscopic image enhancement a very active research field. Due to the intrinsic endoscopic domain characteristics ...
    • Geometric Modeling for Planning of Liver Resection Procedures 

      Palomar, Rafael (Doctoral theses at NTNU;2018:174, Doctoral thesis, 2018)
    • Intra-operative Image Enhancement and Registration for Image Guided Laparoscopic Liver Resection 

      Wang, Congcong (Doctoral theses at NTNU;2020:88, Doctoral thesis, 2020)
    • Multi-Target Tracking and Segmentation for Video Surveillance 

      Ullah, Mohib (Doctoral theses at NTNU;2019:128, Doctoral thesis, 2019)
    • Multiscale deep desmoking for laparoscopic surgery 

      Wang, Congcong; Mohammed, Ahmed Kedir; Alaya Cheikh, Faouzi; Beghdadi, Azeddine; Elle, Ole Jacob (Journal article; Peer reviewed, 2019)
      In minimally invasive surgery, smoke generated by such as electrocautery and laser ablation deteriorates image quality severely. This creates discomfortable view for the surgeon which may increase surgical risk and degrade ...
    • Reviving Traditional Image Quality Metrics Using CNNs 

      Amirshahi, Seyed Ali; Pedersen, Marius; Beghdadi, Azeddine (Journal article; Peer reviewed, 2018)
      Objective Image Quality Metrics (IQMs) are introduced with the goal of modeling the perceptual quality scores given by observers to an image. In this study we use a pre-trained Convolutional Neural Network (CNN) model to ...
    • Towards a video quality assessment based framework for enhancement of laparoscopic videos 

      Khan, Zohaib Amjad; Beghdadi, Azeddine; Alaya Cheikh, Faouzi; Kaaniche, Mounir; Pelanis, Egidijus; Palomar, Rafael; Fretland, Åsmund Avdem; Edwin, Bjørn; Elle, Ole Jacob (Peer reviewed; Journal article, 2020)
      Laparoscopic videos can be affected by different distortions which may impact the performance of surgery and introduce surgical errors. In this work, we propose a framework for automatically detecting and identifying such ...
    • Variational based smoke removal in laparoscopic images 

      Wang, Congcong; Alaya Cheikh, Faouzi; Kaaniche, Mounir; Beghdadi, Azeddine; Elle, Ole Jacob (Journal article; Peer reviewed, 2018)
      Background In laparoscopic surgery, image quality can be severely degraded by surgical smoke, which not only introduces errors for the image processing algorithms (used in image guided surgery), but also reduces the ...