Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 11, 2019
BACKGROUND AND PURPOSE: To investigate a novel markerless prostate localization strategy using a pre-trained deep learning model to interpret routine projection kilovoltage (kV) X-ray images in image-guided radiation therapy (IGRT).
Early diagnosis of sacroiliitis may lead to preventive treatment which can significantly improve the patient's quality of life in the long run. Oftentimes, a CT scan of the lower back or abdomen is acquired for suspected back pain. However, since the...
Classification of benign-malignant lung nodules on chest CT is the most critical step in the early detection of lung cancer and prolongation of patient survival. Despite their success in image classification, deep convolutional neural networks (DCNNs...
PURPOSE: To develop and evaluate a patch-based convolutional neural network (CNN) to generate synthetic computed tomography (sCT) images for magnetic resonance (MR)-only workflow for radiotherapy of head and neck tumors. A patch-based deep learning m...
Automated identification and localization of vertebrae in spinal computed tomography (CT) imaging is a complicated hybrid task. This task requires detecting and indexing a long sequence in a 3-D image, and both image feature extraction and sequence m...
Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many different 2D medical image analysis tasks. In clinical practice, however, a large part of the medical imaging data available is in 3D, e.g, magnetic resonance ima...
Hydrocephalus is a common neurological condition that can have traumatic ramifications and can be lethal without treatment. Nowadays, during therapy radiologists have to spend a vast amount of time assessing the volume of cerebrospinal fluid (CSF) by...
PURPOSE: Manually tracing regions of interest (ROIs) within the liver is the de facto standard method for measuring liver attenuation on computed tomography (CT) in diagnosing nonalcoholic fatty liver disease (NAFLD). However, manual tracing is resou...
RATIONALE AND OBJECTIVES: To evaluate the utility of a convolutional neural network (CNN) with an increased number of contracting and expanding paths of U-net for sparse-view CT reconstruction.
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often leads to a heart attack. It annually causes millions of deaths and billions of dollars in financial losses worldwide. Angiography, which is invasive and risky, is...
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