Abstract: A system and method for performing a medical procedure is provided. The system includes a device having a shaft that generally extends from a proximal end to a distal end along a longitudinal axis. The distal end of the device is configured to identify a topographical profile of a lumen, wherein the topographical profile is determined by traversing the device a distance along the longitudinal axis of the lumen. The device also includes at least one of a plurality of projections movably coupled to the distal end and configured to provide a coupling with the lumen by extending in a direction substantially orthogonal to the longitudinal axis, and at least one radiopaque marker coupled to the distal end and designed to provide a contrast during imaging of the device.

Abstract: A method for determining the three-dimensional location of an object in real-time from a two-dimensional medical image obtained with a medical imaging system is provided. For example, the three-dimensional location of an interventional medical device or a marker positioned on such a device may be determined from a two-dimensional x-ray image obtained with an interventional x-ray imaging system. Template images corresponding to the object under different imaging geometries and orientations are produced and are compared to images acquired with the medical imaging system. Similarity measures, such as normalized cross correlation and normalized similarity integral, are used to determine the similarity between a selected template image and the medical images in different stages of refining the position information for the object.

Abstract: Embodiments disclosed herein provide systems and methods for automating the acquisition and analysis of contrast enhancement images. Model-free discrimination methods are provided in which discrimination between well-perfused pixels (e.g. normal tissue) and perfusion-deficient pixels (e.g. ablation lesions) is automated based on histogram shape. For example, in selected embodiments, discrimination is made based on pixels corresponding to abnormal perfusion (e.g. ablation lesions) and normal perfusion (e.g. normal tissue) form distinctive lobes separated by a minimum formed due to the presence of border pixels. Segmentation of cumulative dynamic contrast enhancement maps by thresholds identified on such histograms is employed to separate abnormally-perfused tissue from the normally-perfused tissue without any user interactions, freeing the user from the necessity to analyze and interpret original dynamic contrast enhancement images or maps derived from them.

Abstract: A method for determining the three-dimensional location of an object in real-time from a two-dimensional medical image obtained with a medical imaging system is provided. For example, the three-dimensional location of an interventional medical device or a marker positioned on such a device may be determined from a two-dimensional x-ray image obtained with an interventional x-ray imaging system. Template images corresponding to the object under different imaging geometries and orientations are produced and are compared to images acquired with the medical imaging system. Similarity measures, such as normalized cross correlation and normalized similarity integral, are used to determine the similarity between a selected template image and the medical images in different stages of refining the position information for the object.

Abstract: Embodiments disclosed herein provide systems and methods for automating the acquisition and analysis of contrast enhancement images. Model-free discrimination methods are provided in which discrimination between well-perfused pixels (e.g. normal tissue) and perfusion-deficient pixels (e.g. ablation lesions) is automated based on histogram shape. For example, in selected embodiments, discrimination is made based on pixels corresponding to abnormal perfusion (e.g. ablation lesions) and normal perfusion (e.g. normal tissue) form distinctive lobes separated by a minimum formed due to the presence of border pixels. Segmentation of cumulative dynamic contrast enhancement maps by thresholds identified on such histograms is employed to separate abnormally-perfused tissue from the normally-perfused tissue without any user interactions, freeing the user from the necessity to analyze and interpret original dynamic contrast enhancement images or maps derived from them.