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We present a self-assessing image-based motion compensation method for coronary roadmapping in fluoroscopic images. Extending our previous work on respiratory motion compensation, we introduce kernel-based nonparametric data analysis in this work to better characterize the objective function involved in motion estimation, which leads to two new improvements in motion compensation. First, through mode...
Brain tumor segmentation is an important image processing step in diagnosis, treatment planning, and follow-up studies of Glioblastoma (GBM). However it is still a challenging task due to varying in size, shape, location, and image intensities within and around the tumor. In this paper, we propose a new brain tumor segmentation method for T1-weighted MR brain images based on an improved level set...
A guidewire is a medical device inserted into vessels during image guided interventions for balloon inflation. During interventions, the guidewire undergoes non-rigid deformation due to patients' breathing and cardiac motions, and such 3D motions are complicated when being projected onto the 2D fluoroscopy. Furthermore, in fluoroscopy there exist severe image artifacts and other wire-like structures...
Thermography captures the temperature distribution of the human skin and is employed in various medical applications. Techniques for automaticaly retrieving medical images based on their content have shown to be useful and are highly sought after. In this paper we show that efficient and effective content-based retrieval of medical thermograms can be performed directly in the compressed domain of...
Computational modeling and simulation of knee joint can help expand our understanding of the knee biomechanics, and thus improve orthopedic practice. Although many computational knee models have been developed, very few of them include a deformable menisci model. In addition, patient specific modeling and simulation are still not widely adopted, although they are shown to be more effective than generic...
Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Performance of medical diagnosis is typically assessed in terms of sensitivity and specificity. In this paper we introduce a pattern classification system for medical diagnosis that is based on fuzzy logic and utilises...
Several popular lossless image compression algorithms were evaluated for the application of compressing medical infrared images. Lossless JPEG, JPEG-LS, JPEG2000, PNG, and CALIC were tested on an image dataset of 380+ thermal images. The results show that JPEG-LS is the algorithm with the best performance, both in terms of compression ratio and compression speed
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