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2016-142 – Surgical training using educational models generally involves explaining surgical techniques through verbalization. This training method can be ineffective for visual learners. Mayo Clinic investigators have developed an augmented reality environment that is designed to provide students with real time verbal and visual feedback. This web-based system projects a trainee’s view of a surgical... Read More
2013-186 – The PET imaging agent F-18 sodium hexafluorophosphate (Na[18F]PF6) for hNIS expression in tumors.
Ultrasound Test Objective for Detection and Characterization of Image Artifacts and Equipment Malfunctions
2010-065 – Some medical payers now require imaging practice accreditation for reimbursement for diagnostic imaging exams, and starting in 2012 this will be true for Medicare patients imaged with MR, CT and nuclear medicine/PET. Accreditation requires regular testing of the performance of the imaging equipment. It is expected that these requirements will apply to ultrasound imaging practices in the near... Read More
2009-275 – Technology Description Neuroradiologists’ ability to successfully interpret MR angiography images is enhanced when projection images called Maximum Intensity Projection (MIP) renderings are independently generated for the three main vascular structures in the head. Currently, this process is performed manually by the MR technician immediately following the acquisition of an MR angiography... Read More
2008-027 – An algorithm has been developed to computationally define significance (in the sense of objects in noisy images which differ significantly from the background noise) in two and three dimensional image volumes. The algorithm uses this definition of significance in the course of reviewing image volumes containing zero mean noise and optional object regions, to automatically and reproducibly... Read More
2008-026 – An algorithm has been developed to automatically define intensity properties for key tissues in magnetic resonance brain images. The algorithm is completely automated in that it does not require that the user provide samples of any tissues, and it does not require that the user provide a brain parenchyma mask. The algorithm is additionally robust in that it is applicable to images acquired... Read More
Algorithm for Identification of Regions of Change in Three Dimensional Magnetic Resonance Brain Images
2006-260 – The algorithm examines serial three dimensional magnetic resonance brain image data and identifies regions which have changed from one acquisition to the next.
2006-258 – The algorithm identifies regions of real signal, and eliminates regions where signal is due only to noise.
2006-257 – Technology Description The comparison of serial MR examinations of the brain is a procedure performed frequently by neuroradiologists for diseases such as tumors, multiple sclerosis, Alzheimer’s disease, and others. The primary objective of such imaging is to detect and characterize any changes. Comparison of serial MR studies of brain-tumor patients is a task whose difficulty is widely... Read More
2005-053 – The shell trajectory is an existing method that is used to acquire MR data. Although to date it has not been as widely used as other methods (e.g., Cartesian acquisition, radial acquisition, or spirals) it has advantages for motion correction and for MR angiography with contrast agents. The current invention is a method to accelerate the shell acquisition by selectively omitting some of the... Read More
2004-263 – A semi-automated computer program to measure joint space width from radiographic images.
2001-013 – A non-iterative motion correction that does not use any navigators is described. It can be used with any 3D application and spirals.
1999-095 – This invention will help allow very high field strength MRI systems to be used safely and effectively as clinical systems for routine patient use.
1998-097 – A method is described that allows both highly sensitive screening for arterial disease in conjuction with highly specific diagnoses on an MR System with high-speed gradients.