This paper aims to address the segmentation and classification of lytic and sclerotic metastatic lesions that are difficult to define by using spinal 3D Computed Tomography (CT) images obtained from highly pathologically affected cases. As the lesion...
IMPORTANCE: Current methods for identifying hospitalized patients at increased risk of delirium require nurse-administered questionnaires with moderate accuracy.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 2, 2018
BACKGROUND: The sudden live changes of stroke survivors may lead to negative psychological and behavioral outcomes, including anxiety and depressive mood, which may compromise the rehabilitation process. Some personality features, such as self-effica...
RATIONALE AND OBJECTIVES: With the growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening, we compare the performance of deep learning computer-aided diagnosis on DBT images to that of conventional full-field digital mammog...
The use of robotic rehabilitation in orthopaedics has been briefly explored. Despite its possible advantages, the use of computer-assisted physiotherapy of patients with musculoskeletal injuries has received little attention. In this paper, we detail...
Purpose To determine the feasibility of using a deep learning approach to detect cartilage lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due to cartilage degeneration, and acute cartilage injury) wit...
Purpose To compare biparametric contrast-free radiomic machine learning (RML), mean apparent diffusion coefficient (ADC), and radiologist assessment for characterization of prostate lesions detected during prospective MRI interpretation. Materials an...
PURPOSE: New software solutions emerged to support radiologists in image interpretation in acute ischemic stroke. This study aimed to validate the performance of computer-aided assessment of the Alberta Stroke Program Early CT score (ASPECTS) for det...
The international journal of cardiovascular imaging
Jul 30, 2018
To explore the diagnostic performance of a machine-learning-based (ML-based) computed fractional flow reserve (cFFR) derived from coronary computed tomography angiography (CCTA) in identifying ischemia-causing lesions verified by invasive FFR in cath...
We developed a computer-aided diagnosis (CADx) method for classification between benign nodule, primary lung cancer, and metastatic lung cancer and evaluated the following: (i) the usefulness of the deep convolutional neural network (DCNN) for CADx o...
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