Browsing NTNU Open by Author "Mohammed, Ahmed Kedir"

Now showing items 1-20 of 21

    • Automated 3D burr detection in cast manufacturing using sparse convolutional neural networks 

      Mohammed, Ahmed Kedir; Kvam, Johannes; Onstein, Ingrid Fjordheim; Bakken, Marianne; Schulerud, Helene (Peer reviewed; Journal article, 2022)
      For automating deburring of cast parts, this paper proposes a general method for estimating burr height using 3D vision sensor that is robust to missing data in the scans and sensor noise. Specifically, we present a novel ...

    • Autonomous subsea intervention (SEAVENTION) 

      Transeth, Aksel Andreas; Schjølberg, Ingrid; Lekkas, Anastasios; Risholm, Petter; Mohammed, Ahmed Kedir; Skaldebø, Martin Breivik; Haugaløkken, Bent Oddvar Arnesen; Bjerkeng, Magnus Christian; Tsiourva, Maria Efstathia; Py, Frédéric (Peer reviewed; Journal article, 2022)
      This paper presents the main results and latest developments in a 4-year project called autonomous subsea intervention (SEAVENTION). In the project we have developed new methods for autonomous inspection, maintenance and ...

    • Computational Techniques for Pathology Detection and Quality Enhancement with emphasis on Colonic Capsule Endoscopy 

      Mohammed, Ahmed Kedir (Doctoral theses at NTNU;2019:351, Doctoral thesis, 2019)

    • Concept-based reasoning in medical imaging 

      Vats, Anuja; Pedersen, Marius; Mohammed, Ahmed Kedir (Peer reviewed; Journal article, 2023)
      Purpose As concept-based reasoning for improving model interpretability becomes promising, the question of how to define good concepts becomes more pertinent. In domains like medical, it is not always feasible to access ...

    • Deep-STRESS Capsule Video Endoscopy Image Enhancement 

      Mohammed, Ahmed Kedir; Pedersen, Marius; Hovde, Øistein; Yildirim Yayilgan, Sule (Journal article; Peer reviewed, 2018)
      This paper proposes a unified framework for capsule video endoscopy image enhancement with an objective to enhance the diagnostic values of these images. The proposed method is based on a hybrid approach of deep learning ...

    • Evaluating clinical diversity and plausibility of synthetic capsule endoscopic images 

      Vats, Anuja; Pedersen, Marius; Mohammed, Ahmed Kedir; Hovde, Øistein (Peer reviewed; Journal article, 2023)
      Wireless Capsule Endoscopy (WCE) is being increasingly used as an alternative imaging modality for complete and non-invasive screening of the gastrointestinal tract. Although this is advantageous in reducing unnecessary ...

    • Fingerphoto Verification Using Siamese Neural Network 

      Madhun, Ahmed Said Mahmoud (Master thesis, 2020)
      De siste årene har vi hatt en enorm utvikling av portable enheter. Sensorene i smart-telefoner og bærbare datamaskiner har kommet til det stadiet at de åpner for nye former for biometrisk autentisering. En av disse formene ...

    • From labels to priors in capsule endoscopy: a prior guided approach for improving generalization with few labels 

      Vats, Anuja; Mohammed, Ahmed Kedir; Pedersen, Marius (Peer reviewed; Journal article, 2022)
      The lack of generalizability of deep learning approaches for the automated diagnosis of pathologies in Wireless Capsule Endoscopy (WCE) has prevented any significant advantages from trickling down to real clinical practices. ...

    • Image Quality Metrics for the Evaluation and Optimization of Capsule Video Endoscopy Enhancement Techniques 

      Pedersen, Marius; Cherepkova, Olga; Mohammed, Ahmed Kedir (Journal article; Peer reviewed, 2017)
      Capsule endoscopy, using a wireless camera to capture the digestive track, is becoming a popular alternative to traditional colonoscopy. The images obtained from a capsule have lower quality compared to traditional ...

    • The Importance Of Skip Connections In Encoder-Decoder Architectures For Colorectal Polyp Detection 

      Mulliqi, Nita; Yildirim Yayilgan, Sule; Mohammed, Ahmed Kedir; Ahmedi, Lule; Wang, Hao; Elezaj, Ogerta; Hovde, Øistein (Chapter, 2020)
      Accurate polyp detection during the colonoscopy procedure impacts colorectal cancer prevention and early detection. In this paper, we investigate the influence of skip connections as the main component of encoder-decoder ...

    • Learning More for Free-A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy 

      Vats, Anuja; Pedersen, Marius; Mohammed, Ahmed Kedir; Hovde, Øistein (Chapter, 2021)
      The progress in Computer Aided Diagnosis (CADx) of Wireless Capsule Endoscopy (WCE) is thwarted by the lack of data. The inadequacy in richly representative healthy and abnormal conditions results in isolated analyses of ...

    • Multichannel Residual Cues for Fine-Grained Classification in Wireless Capsule Endoscopy 

      Vats, Anuja; Raja, Kiran; Pedersen, Marius; Mohammed, Ahmed Kedir (Peer reviewed; Journal article, 2022)
      Early diagnosis of gastrointestinal pathologies leads to timely medical intervention and prevents disease development. Wireless Capsule Endoscopy (WCE) is used as a non-invasive alternative for gastrointestinal examination. ...

    • 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 ...

    • PedNet: A Spatio-Temporal Deep Convolutional Neural Network for Pedestrian Segmentation 

      Ullah, Mohib; Mohammed, Ahmed Kedir; Alaya Cheikh, Faouzi (Journal article; Peer reviewed, 2018)
      Articulation modeling, feature extraction, and classification are the important components of pedestrian segmentation. Usually, these components are modeled independently from each other and then combined in a sequential ...

    • Photo Identification of Individual Salmo trutta Based on Deep Learning 

      Pedersen, Marius; Mohammed, Ahmed Kedir (Peer reviewed; Journal article, 2021)
      Individual fish identification and recognition is an important step in the conservation and management of fisheries. One of most frequently used methods involves capturing and tagging fish. However, these processes have ...

    • PS-DeVCEM: Pathology-sensitive deep learning model for video capsule endoscopy based on weakly labeled data 

      Mohammed, Ahmed Kedir; Farup, Ivar; Pedersen, Marius; Yildirim Yayilgan, Sule; Hovde, Øistein (Peer reviewed; Journal article, 2020)
      We propose a novel pathology-sensitive deep learning model (PS-DeVCEM) for frame-level anomaly detection and multi-label classification of different colon diseases in video capsule endoscopy (VCE) data. Our proposed model ...

    • 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 ...

    • Sparse coded handcrafted and deep features for colon capsule video summarization 

      Mohammed, Ahmed Kedir; Yildirim, Sule; Pedersen, Marius; Hovde, Øistein; Alaya Cheikh, Faouzi (Journal article, 2017)
      Capsule endoscopy, which uses a wireless camera to take images of the digestive track, is emerging as an alternative to traditional wired colonoscopy. A single examination produces a sequence of approximately 50,000 frames. ...

    • Stochastic Capsule Endoscopy Image Enhancement 

      Mohammed, Ahmed Kedir; Farup, Ivar; Pedersen, Marius; Hovde, Øistein; Yildirim Yayilgan, Sule (Journal article; Peer reviewed, 2018)
      Capsule endoscopy, which uses a wireless camera to take images of the digestive tract, is emerging as an alternative to traditional colonoscopy. The diagnostic values of these images depend on the quality of revealed ...

    • StreoScenNet: Surgical stereo robotic scene segmentation 

      Mohammed, Ahmed Kedir; Yildirim Yayilgan, Sule; Farup, Ivar; Pedersen, Marius; Hovde, Øistein (Journal article; Peer reviewed, 2019)
      Surgical robot technology has revolutionized surgery toward a safer laparoscopic surgery and ideally been suited for surgeries requiring minimal invasiveness. Sematic segmentation from robot-assisted surgery videos is an ...