Abstract: Systems and methods for generating images of respective patients from multi-dimensional medical image data sets include a processor circuit in communication with a display having a graphic user interface (GUI), the processor circuit configured to define at least one grouping of a subset of slices selected from slices in a medical data stack, then generate and display at least one slabbed view based on the at least one grouping of slices.

Abstract: A method for reducing an amount of data to be processed in a visualization pipeline. The visualization pipeline includes data capture, data compression, data storage, data decompression, and data rendering including the use of a transfer function. The data is divided into blocks in the compression and the reduction is achieved by adaptively selecting a level-of-detail for each block in the step of decompression utilizing a significance measure based on the transfer function.

Abstract: Visualization systems for rendering images from a multi-dimensional data set, include an interactive visualization system configured to accept user input to define at least one explicit prioritized feature in an image rendered from a multi-dimensional image data set. The at least one prioritized feature is automatically electronically rendered with high or full quality in different interactively requested rendered images of the image data while other non-prioritized features are rendered at lower quality. The visualization system may optionally include a rendering system configured to render images by electronically assigning a level of detail for different tiles associated with an image, each level of detail having a number of pixel samples to be calculated to thereby accelerate image processing.

Abstract: Data retrieval systems for retrieving data from a multidimensional medical data set include: (a) a client configured to electronically request image data of a patient; (b) a server in communication with a plurality of electronically stored multidimensional patient medical image data sets; and (c) a data retrieval interface in communication with the client and the server. The data retrieval interface is configured to retrieve image data from the multidimensional data sets. The respective data sets have a number of grid points in G dimensions and a number of values V for each grid point. Some of the data sets have different G dimensions and V values than others. The data retrieval interface is configured to employ an object oriented retrieval process.

Abstract: Methods and apparatus are configured to provide data to generate and/or render (medical) images using medical volumetric data sets by electronically analyzing a medical volume data set associated with a patient that is automatically electronically divided into a plurality of local histograms having intensity value ranges associated therewith and programmatically generating at least one ?-histogram of data from the local histograms used for at least one of peak detection, transfer function design or adaptation, tissue detection or tissue classification.

Abstract: Systems for rendering images from a multi-dimensional data set include a sensitivity lens configured to electronically render a sequence of images showing features in a region of interest to interrogate and/or explore potential uncertainties in the rendered visualizations of images.

Abstract: A method for reducing an amount of data to be processed in a visualization pipeline. The visualization pipeline includes data capture, data compression, data storage, data decompression, and data rendering including the use of a transfer function. The data is divided into blocks in the compression and the reduction is achieved by adaptively selecting a level-of-detail for each block in the step of decompression utilizing a significance measure based on the transfer function.

Abstract: Systems and methods that visualize medical data having image rendering circuits configured to substantially concurrently display a first image view of breast tissue using a stack of primary tomosynthesis image data and a second image view of breast tissue using a reference image data set, the second image view rendered from at least one of a 2D X-ray mammogram reference image data set or a reference stack of tomosynthesis image data. The first view is visualized based on: (a) anatomical and/or geometric position properties of the reference image data set of the patient; (b) properties of a current view of the reference image data set of the patient; or (c) anatomical and/or geometric position properties of the reference image data set and properties of a current view of the reference image data set.

Abstract: Visualization systems for rendering images from a multi-dimensional data set, include an interactive visualization system configured to accept user input to define at least one explicit prioritized feature in an image rendered from a multi-dimensional image data set. The at least one prioritized feature is automatically electronically rendered with high or full quality in different interactively requested rendered images of the image data while other non-prioritized features are rendered at lower quality. The visualization system may optionally include a rendering system configured to render images by electronically assigning a level of detail for different tiles associated with an image, each level of detail having a number of pixel samples to be calculated to thereby accelerate image processing.

Abstract: Systems, processors and methods display image views of stacks or volume image data and allow a user to navigate the data and/or views using CAD findings.

Abstract: Systems and methods for generating images of respective patients from multi-dimensional medical image data sets include a processor circuit in communication with a display having a graphic user interface (GUI), the processor circuit configured to define at least one grouping of a subset of slices selected from slices in a medical data stack, then generate and display at least one slabbed view based on the at least one grouping of slices.

Abstract: Methods for electronically compressing data from a multidimensional medical data set for long-term storage includes: (a) generating a first medical image from a patient multi-dimensional medical image data set in a short-term storage format; and (b) compressing the patient medical image data set into a long-term storage format using at least one viewing parameter.

Abstract: Methods and apparatus are configured to provide data to generate and/or render (medical) images using medical volumetric data sets by electronically analyzing a medical volume data set associated with a patient that is automatically electronically divided into a plurality of local histograms having intensity value ranges associated therewith and programmatically generating at least one ?-histogram of data from the local histograms used for at least one of peak detection, transfer function design or adaptation, tissue detection or tissue classification.

Abstract: Data retrieval systems for retrieving data from a multidimensional medical data set include: (a) a client configured to electronically request image data of a patient; (b) a server in communication with a plurality of electronically stored multidimensional patient medical image data sets; and (c) a data retrieval interface in communication with the client and the server. The data retrieval interface is configured to retrieve image data from the multidimensional data sets. The respective data sets have a number of grid points in G dimensions and a number of values V for each grid point. Some of the data sets have different G dimensions and V values than others. The data retrieval interface is configured to employ an object oriented retrieval process.

Abstract: Methods and apparatus are configured to provide data to render (medical) images using direct volume rendering by electronically analyzing a medical volume data set associated with a patient that is automatically electronically divided into a plurality of local histograms having intensity value ranges associated therewith and programmatically generating data used for at least one of tissue detection or tissue classification of tissue having overlapping intensity values.