Computer methods and programs in biomedicine
Jun 7, 2023
UNLABELLED: Backgound and Objective: Deep learning-based segmentation of the liver and hepatic lesions therein steadily gains relevance in clinical practice due to the increasing incidence of liver cancer each year. Whereas various network variants w...
BACKGROUND: Facing the 0.7-22% incidence rate of hepatocellular carcinoma (HCC) with inferior vena cava tumor thrombus (IVCTT), there are usually no obvious symptoms and signs when the tumor thrombus completely blocks the IVCTT in the early stage.1.J...
BACKGROUND: Identification of resections with high risk of intraoperative complications is critical in guiding case selection for minimally invasive liver surgery. Several Japanese and European difficulty scoring systems have been proposed for laparo...
International journal of computer assisted radiology and surgery
May 30, 2023
PURPOSE: Accuracy of image-guided liver surgery is challenged by deformation of the liver during the procedure. This study aims at improving navigation accuracy by using intraoperative deep learning segmentation and nonrigid registration of hepatic v...
PURPOSE: Liver Imaging Reporting and Data System (LI-RADS) is limited by interreader variability. Thus, our study aimed to develop a deep-learning model for classifying LI-RADS major features using subtraction images using magnetic resonance imaging ...
OBJECTIVES: To qualitatively and quantitatively compare a single breath-hold fast half-Fourier single-shot turbo spin echo sequence with deep learning reconstruction (DL HASTE) with T2-weighted BLADE sequence for liver MRI at 3 T.
OBJECTIVES: Machine learning (ML) for medical imaging is emerging for several organs and image modalities. Our objectives were to provide clinicians with an overview of this field by answering the following questions: (1) How is ML applied in liver c...
INTRODUCTION: Robotic surgery has been increasingly utilized, yet its application for hepato-pancreato-biliary (HPB) procedures remains low due to technical complexity, perceived financial burden, and unproven clinical benefits. We hypothesized that ...
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