Abstract: A variety of systems, methods, and articles of manufacture are disclosed. An example includes accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; identifying a trend in the patient deviation scores for at least one clinical parameter; generating of a report including a visual indication of the trend; and outputting of the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of

Abstract: Methods and apparatus for determining brain cortical thickness are provided. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Abstract: A system and method for analyzing and visualizing a local feature of interest includes access of a clinical image dataset comprising clinical image data acquired from a patient, identification of a region of interest (ROI) from the clinical image dataset, and extraction of at least one local feature corresponding to the ROI. The system and method also include definition of a local feature dataset comprising data representing at least one local feature, access of a pre-computed reference dataset comprising image data representing an expected value of the at least one identified derived characteristic of interest, and comparison of the characteristic dataset to the pre-computed reference dataset. Further, the system and method include calculation of at least one deviation metric from the comparison and output of a visualization of the at least one deviation metric.

Abstract: A system and method for analyzing and visualizing a local feature of interest includes access of a clinical image dataset comprising clinical image data acquired from a patient, identification of a region of interest (ROI) from the clinical image dataset, and extraction of at least one local feature corresponding to the ROI. The system and method also include definition of a local feature dataset comprising data representing at least one local feature, access of a pre-computed reference dataset comprising image data representing an expected value of the at least one identified derived characteristic of interest, and comparison of the characteristic dataset to the pre-computed reference dataset. Further, the system and method include calculation of at least one deviation metric from the comparison and output of a visualization of the at least one deviation metric.

Abstract: A system comprising a memory device having a plurality of routines stored therein, a processor configured to execute the plurality of routines stored in the memory device, the plurality of routines comprising: a routine configured to effect, when executed, accessing of patient deviation scores indicative of differences between patient data and reference data representative of a population segment, wherein the patient deviation scores are derived from longitudinal data of the patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data; a routine configured to effect, when executed, identifying a trend in the patient deviation scores for at least one clinical parameter; a routine configured to effect, when executed, generating of a report including a visual indication of the trend; and a routine configured to effect, when executed, outputting of

Abstract: A system and method for detecting, diagnosing, and monitoring a disease and determining a disease signature including accessing patient deviation scores indicative of differences between patient data and reference data representative of a population segment, the patient deviation scores derived from longitudinal patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data. The system and method also includes identifying a trend in the patient deviation scores for at least one clinical parameter, generating a report including a visual indication of the trend, and outputting the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: A system and method for detecting, diagnosing, and monitoring a disease and determining a disease signature including accessing patient deviation scores indicative of differences between patient data and reference data representative of a population segment, the patient deviation scores derived from longitudinal patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data. The system and method also includes identifying a trend in the patient deviation scores for at least one clinical parameter, generating a report including a visual indication of the trend, and outputting the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: A system and method for detecting, diagnosing, and monitoring a disease and determining a disease signature including accessing patient deviation scores indicative of differences between patient data and reference data representative of a population segment, the patient deviation scores derived from longitudinal patient data such that the patient deviation scores include a plurality of sets of patient deviation scores, each set indicative of differences between patient data collected at a respective point in time and the reference data. The system and method also includes identifying a trend in the patient deviation scores for at least one clinical parameter, generating a report including a visual indication of the trend, and outputting the report. The report includes one or more views including Z, T, D, DT, and D feedback on T views, using image and non-image data.

Abstract: Methods and apparatus for determining brain cortical thickness. One method includes determining an intensity profile at each of a plurality of cortical surface points of an imaged brain using brain tissue image data and calculating a cortical thickness based on a parametrically determined transition point of each intensity profile.

Abstract: In a dose modulation method, transmission tomographic imaging data of an associated imaging subject are acquired using a radiation source (14) revolving around the associated imaging subject. During the tomographic imaging, an estimated attenuation of radiation is determined for an upcoming position or angular bin (721, 82) of the revolving radiation source based on attenuations determined at previously acquired positions or angular bins (701, 84, 90) of the radiation source. Prior to acquiring tomographic imaging data at the upcoming position or angular bin, a level of radiation produced by the radiation source is adjusted based on the estimated attenuation of radiation.

Abstract: In a dose modulation method, transmission tomographic imaging data of an associated imaging subject are acquired using a radiation source (14) revolving around the associated imaging subject. During the tomographic imaging, an estimated attenuation of radiation is determined for an upcoming position or angular bin (721, 82) of the revolving radiation source based on attenuations determined at previously acquired positions or angular bins (701, 84, 90) of the radiation source. Prior to acquiring tomographic imaging data at the upcoming position or angular bin, a level of radiation produced by the radiation source is adjusted based on the estimated attenuation of radiation.

Abstract: An adaptive median filter (40) provides dynamic detection and correction of digital image defects which are caused by defective or malfunctioning elements of a radiation detector array (20). The adaptive median filter receives (100) lines of pixel values of a digital image that may have defects and a user-defined defect threshold. The lines of pixel values are scanned on a pixel-by-pixel basis using a kernel of n×n pixels, where the kernel contains the candidate pixel being examined (120). Each kernel is numerically reordered (130) and a median value is calculated (140). A defect threshold value is calculated by multiplying the user-defined defect threshold criteria and the candidate pixel value (150). A reference value is calculated by subtracting the candidate pixel value and the median value (160). The reference value is compared to the defect threshold value (170).

Abstract: A CT scanner (10) for obtaining a medical diagnostic image of a subject includes a stationary gantry (12), and a rotating gantry (14). The detected radiation is reconstructed and divided into sub-portions, which sub-portions are aligned by a registration processor (56). The registered images are stored in a high resolution memory (58) and a maximum artery enhancement value is calculated from the high resolution images. A resolution reducer (82) reduces the resolution of the high resolution images. Time-density curves are found for the voxels of the images, which time-density curves are truncated to eliminate unwanted data, and analyzed to determine characteristic values. A perfusion calculator (106) calculates perfusion by using the maximum artery enhancement value and the characteristic values. A diagnostician can view any one of a low resolution image, a high resolution image, and a perfusion image on a video monitor (112).

Abstract: A The medical diagnostic imaging apparatus includes a source (12) for generating x-rays, an image receptor (26) for receiving the x-rays and generating image data, and an image processing subsystem (6) for generating corrected image data from the image data acquired by the image receptor. The image processing subsystem includes a processor (46) that is programmed to generate noise image data (54) by high-pass filtering (52) uncorrected diagnostic image data acquired by the image receptor, to determine statistical data (64, 66) from a first subset (56) of the noise image data, and to correct a subset (36) of the uncorrected diagnostic image data based on the statistical data, the subset of the uncorrected diagnostic image data corresponding to the subset of the noise image data.

Abstract: A CT scanner (10) for obtaining a medical diagnostic image of a subject includes a stationary gantry (12), and a rotating gantry (14) rotatably supported on the stationary gantry (12) for rotation about the subject. In a perfusion study 130 time-density curves of voxels of an imaging region are computed. In a low signal identification step (132), all voxels with low signal are identified. In a clustering step (134), low signal voxels are clustered together. In a representative determination step (136) representative time-density curves are computed. In a functional measurement step (138), measurements are calculated from the combined and uncombined time-density values. In an assigning step (140), each low signal voxel is assigned the values determined for its group. In a combining step (142) the results of the low and normal signal voxels are combined to produce a single functional perfusion image.

Abstract: A CT scanner (10) for obtaining a medical diagnostic image of a subject includes a stationary gantry (12), and a rotating gantry (14) rotatably supported on the stationary gantry (12) for rotation about the subject. A plurality of temporally displaced volume images are gathered, divided into slices, and stored in slice memories (541, 542, . . . 54n). A slice comparitor (58) compares each slice to a selected reference slice. The slices are transformed by a slice transformer (60) to align the slices thereby correcting for movement of the subject over the scan period.