Abstract: A method for electronically removing a lesion from a three-dimensional (3D) medical image includes segmenting each two-dimensional (2D) slice of a sequence of 2D slices of the 3D medical image to identify the lesion within any one or more of the 2D slices. The method includes deleting the lesion from each 2D slice in which the lesion was identified to create a sequence of lesion-deleted slices. The method includes constructing, based on the sequence of lesion-deleted slices, a lesion-deleted intensity-based projection image, such as a lesion-deleted maximum-intensity projection image. Advantageously, the method improves the accuracy of background parenchymal enhancement (BPE) by excluding high-intensity voxels that indicate the presence of a lesion, and thus are not indicative of BPE.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.

Abstract: An image array includes pixels, each representing an image-based feature value of a patient obtained from imaging. The array includes first and second dimensions. Pixels corresponding to a specific patient of a plurality of patients extend in the first dimension and pixels corresponding to a specific feature of a plurality of features extend in the second dimension. Patients represented in the image array are grouped into two or more groups. Each indicates a known condition, such that patients having a first and second conditions are respectively part of a first and a second group and are in a first and a second portion of the array, respectively. The groups are separately organized according to a selected feature. Patients of the first and second groups are respectively arranged in an order of values for the selected feature within the first and second portions.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.

Abstract: A method and apparatus for reconstruction of a region of interest (ROI) for an object using an imaging system is provided. The imaging system may substantially exactly reconstruct the ROI with a straight line trajectory. In the straight line trajectory, the ROI is not bounded or encircled by the actual trajectory of the source (e.g., no chords that are composed from two points on the source trajectory intersect or fill the ROI to be imaged). However, the ROI may be substantially reconstructed by using “virtual” chords to reconstruct the ROI. The virtual chords are such that no point on the trajectory is included in the virtual chord (such as one that is parallel to the straight line trajectory). These virtual chords may intersect and fill the ROI, thus enabling substantially exact reconstruction. Further, in reconstructing the image, the straight line trajectory may be assumed to be infinite in length.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.

Abstract: A method, system, and computer software product for analyzing medical images, including obtaining image data representative of a plurality of medical images of the abnormality, each medical image corresponding to an image of the abnormality acquired at a different time relative to a time of administration of a contrast medium, each medical image including a predetermined number of voxels; partitioning each medical image into at least two groups based on the obtained image data, wherein each group corresponds to a subset of the predetermined number of voxels, and each group is associated with a temporal image pattern in the plurality of medical images; selecting, from among the temporal patterns, an enhancement temporal pattern as representative of the abnormality; and determining, based on the selected temporal pattern, a medical state of the abnormality.

Abstract: A method, system, and computer software product for correlating medical images, comprising: obtaining first image data representative of a first medical image including a first abnormality; obtaining second image data representative of a second medical image including a second abnormality; determining at least one feature value for each of the first and second abnormalities using the first and second image data; calculating, based on the determined feature values, a likelihood value indicative of a likelihood that the first and second abnormalities are a same abnormality; and outputting the determined likelihood value.

Abstract: A method for computer-assisted interpretation of medical images that factor in characteristics of an individual performing the interpretation. The method automatically determines and/or incorporates prevalence-based computer analysis based on an estimated likelihood of a pathological state, e.g., a malignancy. A system implementing the method includes the calculation of features or other characteristics of images in a known database, calculation of features of an unknown case, calculation of the probability (or likelihood) of disease state, calculation of the modified computer output that includes the internal prevalence (or internal decision-making process) of the user (or group of users), and output of the result.