PURPOSE: Automatic liver segmentation from abdominal computed tomography (CT) images is a fundamental task in computer-assisted liver surgery programs. Many liver segmentation algorithms are very sensitive to fuzzy boundaries and heterogeneous pathol...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2021
Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and radiation treatment planning (RTP). Disadvantages of CT include poor soft tissue contrast and exposure to ionizing radiation. While MRI can overcome the...
Deep learning for three dimensional (3D) abdominal organ segmentation on high-resolution computed tomography (CT) is a challenging topic, in part due to the limited memory provide by graphics processing units (GPU) and large number of parameters and ...
PURPOSE: Pancreas segmentation is a difficult task because of the high intrapatient variability in the shape, size, and location of the organ, as well as the low contrast and small footprint of the CT scan. At present, the U-Net model is likely to le...
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Nov 3, 2020
PURPOSE: The aim of this study was to develop an algorithm for automated estimation of patient height and weight during computed tomography (CT) and to evaluate its accuracy in everyday clinical practice.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Oct 17, 2020
PURPOSE: Artificial intelligence (AI) can play a significant role in Magnetic Resonance guided Radiotherapy (MRgRT), especially to speed up the online adaptive workflow. The aim of this study is to set up a Deep Learning (DL) approach able to generat...
PURPOSE: Volumetric pancreas segmentation can be used in the diagnosis of pancreatic diseases, the research about diabetes and surgical planning. Since manual delineation is time-consuming and laborious, we develop a deep learning-based framework for...