Abstract: A method for performing image registration is provided. The method comprises obtaining a reference image dataset and a target image dataset and defining an image mask for a region of interest in the reference image dataset. The method further comprises registering a corresponding region of interest in the target image dataset with the image mask, using a similarity metric, wherein the similarity metric is computed based on one or more voxels in the region of interest defined by the image mask.

Abstract: Methods and systems and computer program products for automatically segmenting the volume of interest from intensity images are provided. The method for segmenting a volume of interest in an intensity image receives the intensity image and the scanner acquisition parameters used to acquire the intensity image. The method then scales the contrast of the intensity image based, at least in part, on the scanner acquisition parameters. The method segments the intensity image based, at least in part, on image data of the intensity image and the scanner acquisition parameters, to obtain the volume of interest.

Abstract: A method of imaging is presented. The method includes reconstructing image data acquired at a plurality of time intervals to obtain a plurality of images. Further, the method includes generating a mean image using the plurality of images. The method also includes correcting motion in the mean image or the plurality of images or both the mean image and the plurality of images by iteratively determining convergence of the mean image or the plurality of images or both the mean image and the plurality of images to generate a converged mean image, a converged plurality of images, or both a converged mean image and a converged plurality of images.

Abstract: A method is provided for identifying a location of a region of interest in a volumetric image scan that includes a plurality of slices of an object and wherein each slice, in turn, includes a plurality of pixels. The method includes setting a predetermined pixel intensity threshold corresponding to a particular region of interest; identifying target pixels for each slice from the plurality of pixels that exceed the predetermined pixel intensity threshold; creating an energy profile from the target pixels for each slice; and comparing the energy profile to a predefined energy profile to determine the location of the region of interest.

Abstract: A method and apparatus are provided for reducing motion related imaging artifacts. The method includes determining an internal motion for of two regions of the object, each region having a different level of motion, scanning the first region using a first scan protocol based on the motion, scanning a second region using a second different scan protocol based on the motion, and generating an image of the object based on the first and second regions.

Abstract: A method is provided for generating a metavolume for reconstructing an image. The method provides for acquiring a plurality of low-resolution images of an imaged volume, the plurality of low-resolution images obtained from one or more imaging planes and merging the plurality of low-resolution images using a statistical operation to generate a metavolume. Systems and computer programs that afford functionality of the type defined by this method may be provided by the present technique.

Abstract: An apparatus, system and method to determine a coordinate system of a heart includes an imager and a computer. The computer is programmed to acquire a first set of initialization imaging data from an anatomical region of a free-breathing subject. A portion of the first set of initialization imaging data includes organ data, which includes cardiac data. The computer is further programmed to determine a location of a central region of a left ventricle of a heart, where the location is based on the organ data and a priori information. The computer is also programmed to determine a short axis of the left ventricle based on the determined location, acquire a first set of post-initialization imaging data from the free-breathing subject from an imaging plane orientation based on the determination of the short axis, and reconstruct at least one image from the first set of post-initialization imaging data.

Abstract: A technique is provided for automatically generating a bone mask in CTA angiography. In accordance with the technique, an image data set may be pre-processed to accomplish a variety of function, such as removal of image data associated with the table, partitioning the volume into regionally consistent sub-volumes, computing structures edges based on gradients, and/or calculating seed points for subsequent region growing. The pre-processed data may then be automatically segmented for bone and vascular structure. The automatic vascular segmentation may be accomplished using constrained region growing in which the constraints are dynamically updated based upon local statistics of the image data. The vascular structure may be subtracted from the bone structure to generate a bone mask. The bone mask may in turn be subtracted from the image data set to generate a bone-free CTA volume for reconstruction of volume renderings.

Abstract: A method for performing image registration is provided. The method comprises obtaining a reference image dataset and a target image dataset and defining an image mask for a region of interest in the reference image dataset. The method further comprises registering a corresponding region of interest in the target image dataset with the image mask, using a similarity metric, wherein the similarity metric is computed based on one or more voxels in the region of interest defined by the image mask.

Abstract: The present technique provides a system and method for processing an image. Particularly the method comprises acquiring image data in frequency space (k-space) of an imaged volume and obtaining a three-dimensional (3-D) k-space volume representative of the imaged volume based on the acquired k-space data. The method further comprises selecting a two-dimensional (2-D) plane from the 3-D k-space volume and applying an inverse Fourier transform to the selected 2-D plane to obtain a real 2-D X-ray-like (or enhanced rendering) projection of the imaged volume offering insights into the 3-D data.

Abstract: A method is provided for identifying a location of a region of interest in a volumetric image scan that includes a plurality of slices of an object and wherein each slice, in turn, includes a plurality of pixels. The method includes setting a predetermined pixel intensity threshold corresponding to a particular region of interest; identifying target pixels for each slice from the plurality of pixels that exceed the predetermined pixel intensity threshold; creating an energy profile from the target pixels for each slice; and comparing the energy profile to a predefined energy profile to determine the location of the region of interest.

Abstract: The present technique provides a system and method for processing an image. Particularly the method comprises acquiring image data in frequency space (k-space) of an imaged volume and obtaining a three-dimensional (3-D) k-space volume representative of the imaged volume based on the acquired k-space data. The method further comprises selecting a two-dimensional (2-D) plane from the 3-D k-space volume and applying an inverse Fourier transform to the selected 2-D plane to obtain a real 2-D X-ray-like (or enhanced rendering) projection of the imaged volume offering insights into the 3-D data.

Abstract: A technique for automatically labeling a CT image of the brain with anatomical information. The anatomical information is obtained from an atlas of the brain prepared from an MR image of the brain. The atlas contains image data that is referenced to the Talairach coordinate system. The atlas is aligned to the CT image and the coordinate system of the CT image data is transformed to the Talairach coordinate system. The alignment of the CT image and the atlas is performed using anatomical landmarks that are visible on both the CT image and the atlas. The CT image is then labeled automatically with the anatomical information in the atlas.

Abstract: A technique is provided for utilizing a model of an anatomical feature to facilitate the segmentation of the anatomical feature from its background in a medical image. A global alignment of the model with a region in the patient's image data that generally corresponds to the anatomical feature is performed in one embodiment. Internal structural features within the model are then aligned with their corresponding structural features in the patient's image data. The portion of the patient's image data that is aligned with the model of the anatomical feature is then segmented from the remaining portions of the patient's image data that are not aligned with the model.

Abstract: A moving image is aligned with a fixed image by an initial gross alignment, followed by identification of particular regions or blobs in the moving image. The blobs may be selected based upon particular features in regions of the image, such as anatomical features in a medical image. Blob matching is performed between the selected blobs and the fixed image, and transforms are developed for displacement of the matched blobs. Certain blobs may be dropped from the selection to enhance performance. Individual transformations for individual pixels or voxels in the moving image are then interpolated from the transforms for the blobs.

Abstract: A technique is provided for segmenting a structure of interest from a volume dataset. The technique identifies regions of the structure using templates having characteristics of the structure of interest. The identified regions may then undergo a constrained growth process using dynamic constraints that may vary based on local statistics associated with the identified structure regions. Edges within the volume may be determined using gradient data determined by evaluating the strongest gradient between each pixel and all adjacent pixels. The edge data may be used to prevent the constrained growing process from exceeding the boundaries of the structure of interest.

Abstract: A method for imaging is presented. The method includes receiving a first image data set and at least one other image data set. Further the method includes adaptively selecting corresponding regions of interest in each of the first image data set and the at least one other image data set based upon apriori information associated with each of the first image data set and the at least one other image data set. Additionally, the method includes selecting a customized registration method based upon the selected regions of interest and the apriori information corresponding to the selected regions of interest. The method also includes registering each of the corresponding selected regions of interest from the first image data set and the at least one other image data set employing the selected registration method.

Abstract: A technique is provided for partitioning an imaged volume into two or more sub-volumes. The technique identifies partition lines which separate the sub-volumes by generating a profile, such as a bone profile, which is then analyzed to determine the placement of the partition lines. In one embodiment, placement of the partition lines is determined automatically by applying one or more sets of hierarchical rules to the profile. After separation of the imaged volume into sub-volumes, each sub-volume may be differentially segmented such that segmentation is customized for the sub-volume. Likewise, after separation of the imaged volume into sub-volumes, the acquisition parameters for each sub-volume may be customized for subsequent acquisitions.

Abstract: A technique is provided for automatically identifying regions of bone or other structural regions within a reconstructed CT volume data set. The technique identifies and labels regions within the data set and computes various statistics for the regions. A rule-based classifier processes the statistics to classify each region. Incidental connections between disparate regions are eliminated. A structure mask, such as a bone mask, is then constructed after exclusion of regions of interest, such as a vascular map. The structure mask may then be used to construct a volume rendering free of the structure, such as bone-free.

Abstract: Systems and methods for interacting effectively with three-dimensional data are provided such that a data acquisition system of an imaging system can be guided appropriately to gather relevant information from the object being imaged. In one embodiment, the imaging system includes the data acquisition system for obtaining a three-dimensional image of the object; and a processor coupled to the data acquisition system. The processor may be configured for receiving a user interface input based on interaction with the three-dimensional image, and for providing multiple parameters to the data acquisition system based on the user interface input. These parameters may be used for further acquisition by the data acquisition system.