Blar i SINTEF Open på forfatter "Lindseth, Frank"

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    • 3D ultrasound reconstruction algorithms from analog and digital data 

      Solberg, Ole Vegard; Lindseth, Frank; Bø, Lars Eirik; Muller, Sebastien; Meland, Janne Beate Lervik; Tangen, Geir Arne; Hernes, Toril A. Nagelhus (Journal article; Peer reviewed, 2011)

    • 3D ultrasound-guided resection of low-grade gliomas: principles and clinical examples 

      Unsgård, Geirmund; Lindseth, Frank (Journal article, 2019)
      3D ultrasound (US) is a convenient tool for guiding the resection of low-grade gliomas, seemingly without deterioration in patients’ quality of life. This article offers an update of the intraoperative workflow and the ...

    • Airway segmentation and centerline extraction from thoracic CT - Comparison of a new method to state of the art commercialized methods 

      Reynisson, Pall Jens; Scali, Marta; Smistad, Erik; Hofstad, Erlend Fagertun; Leira, Håkon Olav; Lindseth, Frank; Hernes, Toril A. Nagelhus; Amundsen, Tore; Sorger, Hanne; Langø, Thomas (Journal article; Peer reviewed, 2015)
      Introduction Our motivation is increased bronchoscopic diagnostic yield and optimized preparation, for navigated bronchoscopy. In navigated bronchoscopy, virtual 3D airway visualization is often used to guide a bronchoscopic ...

    • Automatic Intraoperative Correction of Brain Shift for Accurate Neuronavigation 

      Iversen, Daniel Høyer; Wein, Wolfgang; Lindseth, Frank; Unsgård, Geirmund; Reinertsen, Ingerid (Journal article; Peer reviewed, 2018)
      Background Unreliable neuronavigation owing to inaccurate patient-to-image registration and brain shift is a major problem in conventional magnetic resonance imaging–guided neurosurgery. We performed a prospective ...

    • 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 ...

    • Laboratory test of Single Landmark registration method for ultrasound-based navigation in laparoscopy using an open-source platform 

      Perez de Frutos, Javier; Hofstad, Erlend Fagertun; Solberg, Ole Vegard; Tangen, Geir Arne; Lindseth, Frank; Langø, Thomas; Elle, Ole Jacob; Mårvik, Ronald (Journal article; Peer reviewed, 2018)
      Purpose Test the feasibility of the novel Single Landmark image-to-patient registration method for use in the operating room for future clinical trials. The algorithm is implemented in the open-source platform CustusX, a ...

    • Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation 

      Perez de Frutos, Javier; Pedersen, Andre; Pelanis, Egidijus; Bouget, David Nicolas Jean-Mar; Survarachakan, Shanmugapriya; Langø, Thomas; Elle, Ole Jakob; Lindseth, Frank (Peer reviewed; Journal article, 2023)
      Purpose: This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. Methods: Different training strategies, loss functions, ...

    • Procedural Medical Training in VR in a Smart Virtual University Hospital 

      Snarby, Håvard; Gåsbakk, Tarald; Prasolova-Førland, Ekaterina; Steinsbekk, Aslak; Lindseth, Frank (Smart Education and e-Learning;2018, Chapter; Peer reviewed, 2018)
      A smart virtual university hospital representing a real-life one, can prepare students for direct patient contact and provide possibilities for clinical practice. Such a virtual hospital will support student learning by ...

    • Teacher-student approach for lung tumor segmentation from mixed-supervised datasets 

      Fredriksen, Vemund; Sevle, Svein Ole M.; Pedersen, André; Langø, Thomas; Kiss, Gabriel; Lindseth, Frank (Peer reviewed; Journal article, 2022)
      Purpose: Cancer is among the leading causes of death in the developed world, and lung cancer is the most lethal type. Early detection is crucial for better prognosis, but can be resource intensive to achieve. Automating ...

    • Versatile robotic probe calibration for position tracking in ultrasound imaging 

      Bø, Lars Eirik; Hofstad, Erlend Fagertun; Lindseth, Frank; Hernes, Toril A. Nagelhus (Journal article; Peer reviewed, 2015)
      Within the field of ultrasound-guided procedures, there are a number of methods for ultrasound probe calibration. While these methods are usually developed for a specific probe, they are in principle easily adapted to other ...