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Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologistpsilas observations on the patientpsilas medical conditions in the associated medical images. However, as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and(More)
Numerous studies addressing different methods of head injury prognostication have been published. Unfortunately, these studies often incorporate different head injury prognostication models and study populations, thus making direct comparison difficult, if not impossible. Furthermore, newer artificial intelligence tools such as machine learning methods have(More)
Modern image-guided spinal navigation employs high-quality intra-operative three dimensional (3D) images to improve the accuracy of spinal surgery. This study aimed to assess the accuracy of thoraco-lumbar pedicle screw insertion using the O-arm (Breakaway Imaging, LLC, Littleton, MA, USA) 3D imaging system. Ninety-two patients underwent insertion of(More)
A method for automatic classification of computed tomography (CT) brain images of different head trauma types is presented in this paper. The method has three major steps: 1. The images are first segmented to find potential hemorrhage regions using ellipse fitting, background removal and wavelet decomposition technique; 2. For each region, features (such as(More)
In intracranial pathological examinations using CT scan, brain midline shift (MLS) is an important diagnostic feature indicating the pathological severity and patient's survival possibility. In this paper, we develop a new method of tracing the brain midline shift in traumatic brain injury (TBI) CT images using its original cause - the hemorrhage. Firstly,(More)
Brain midline shift (MLS) is a significant factor in brain CT diagnosis. In this paper, we present a new method of automatically detecting and quantifying brain midline shift in traumatic injury brain CT images. The proposed method automatically picks out the CT slice on which midline shift can be observed most clearly and uses automatically detected(More)
Multi-slice Computer Tomography (CT) scans are widely used in today's diagnosis of head traumas. It is effective to disclose the bleeding and fractures. In this paper, we present an automated detection of CT scan slices which contain hemorrhages. Our method is robust towards various rotation, displacement and motion blur. Detection of these pathological(More)
Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction.(More)
Automatic medical image classification is difficult because of the lacking of training data. As manual labeling is too costly, we provide an automatic labeling solution to this problem by making use of the radiology report associated with the medical images. We first segment and reconstruct the 3D regions of interest (ROIs) from the medical images, and(More)
Of the 206 patients who contracted Severe Acute Respiratory Syndrome (SARS) in Singapore five developed large artery cerebral infarctions. Four patients were critically-ill and three died. Intravenous immunoglobulin was given to three patients. An increased incidence of deep venous thrombosis and pulmonary embolism was also observed among the critically-ill(More)