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Currently, Compressive Tracking (CT) method has drawn great attention because of its high efficiency. However, it cannot well deal with some appearance variations due to its limitations of feature expression and it only uses a fixed parameter to update the appearance model. In order to handle such matters, we propose an adaptive CT method that combines the predicted target position with CT based on...
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 extract pathology and anatomy information from...
A near-field imaging method based on the Non-uniform fast Fourier transformation (NUFFT) is presented. The NUFFT is incorporated in the computed tomography (CT) method in replace of the inverse fast Fourier transformation (IFFT) and the one-dimensional (1-D) interpolation. Comparisons with the conventional near-field filtered back projection (FBP) method are performed. Simulations demonstrate that...
Computed tomography (CT) is used widely in traumatic brain injury diagnosis. One axial brain CT scan consists of multiple slices with different heights along the brain axial direction. Indexing of brain CT slices is to order the slices and align each individual slice onto the corresponding brain axial height, which is an important step in content-based image retrieval and computer-assisted diagnosis...
Large number of medical images are produced daily in hospitals and medical institutions, the needs to efficiently process, index, search and retrieve these images are great. In this paper, we propose a pathology based medical image annotation framework using a statistical machine translation approach. After pathology terms and regions of interest (ROIs) are extracted from training text and images...
Approximately ten million people in the world suffer from traumatic brain injury (TBI) each year. A total of $60 billion cost due to TBI was estimated in the United States in year 2000. To reduce the burden more clinical research and education are required. In this study we developed MiBank, a web-based integrated TBI information system, to enable rapid access to both digital images and associated...
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, we model the relationship between the hemorrhage...
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 used, unless proper text mining has been...
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