Zhongmin Steve Lin - Solon OH Shalabh Chandra - Twinsburg OH
Assignee:
Koninklijke Philips Electronics, N.V. - Eindhoven
International Classification:
G01N 2304
US Classification:
378 62, 378 8
Abstract:
A CT scanner ( ) for obtaining a medical diagnostic image of a subject includes a stationary gantry ( ), and a rotating gantry ( ) rotatably supported on the stationary gantry ( ) for rotation about the subject. A plurality of temporally displaced volume images are gathered, divided into slices, and stored in slice memories ( ). A slice comparitor ( ) compares each slice to a selected reference slice. The slices are transformed by a slice transformer ( ) to align the slices thereby correcting for movement of the subject over the scan period.
Scott Kenneth Pohlman - Willoughby OH Zhongmin Steve Lin - Solon OH
Assignee:
Koninklijke Philips Electronics, N.V. - Eindhoven
International Classification:
A61B 600
US Classification:
378 4, 378 8, 378 19, 378901, 382131
Abstract:
A CT scanner ( ) for obtaining a medical diagnostic image of a subject includes a stationary gantry ( ), and a rotating gantry ( ) rotatably supported on the stationary gantry ( ) for rotation about the subject. In a perfusion study time-density curves of voxels of an imaging region are computed. In a low signal identification step ( ), all voxels with low signal are identified. In a clustering step ( ), low signal voxels are clustered together. In a representative determination step ( ) representative time-density curves are computed. In a functional measurement step ( ), measurements are calculated from the combined and uncombined time-density values. In an assigning step ( ), each low signal voxel is assigned the values determined for its group. In a combining step ( ) the results of the low and normal signal voxels are combined to produce a single functional perfusion image.
Method And Apparatus For Reducing Noise Artifacts In A Diagnostic Image
A The medical diagnostic imaging apparatus includes a source ( ) for generating x-rays, an image receptor ( ) for receiving the x-rays and generating image data, and an image processing subsystem ( ) for generating corrected image data from the image data acquired by the image receptor. The image processing subsystem includes a processor ( ) that is programmed to generate noise image data ( ) by high-pass filtering ( ) uncorrected diagnostic image data acquired by the image receptor, to determine statistical data ( ) from a first subset ( ) of the noise image data, and to correct a subset ( ) 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.
A CT scanner ( ) for obtaining a medical diagnostic image of a subject includes a stationary gantry ( ), and a rotating gantry ( ). The detected radiation is reconstructed and divided into sub-portions, which sub-portions are aligned by a registration processor ( ). The registered images are stored in a high resolution memory ( ) and a maximum artery enhancement value is calculated from the high resolution images. A resolution reducer ( ) 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 ( ) 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 ( ).
Method And Apparatus For Digital Image Defect Correction And Noise Filtering
An adaptive median filter ( ) provides dynamic detection and correction of digital image defects which are caused by defective or malfunctioning elements of a radiation detector array ( ). The adaptive median filter receives ( ) 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 nÃn pixels, where the kernel contains the candidate pixel being examined ( ). Each kernel is numerically reordered ( ) and a median value is calculated ( ). A defect threshold value is calculated by multiplying the user-defined defect threshold criteria and the candidate pixel value ( ). A reference value is calculated by subtracting the candidate pixel value and the median value ( ). The reference value is compared to the defect threshold value ( ).
In a dose modulation method, transmission tomographic imaging data of an associated imaging subject are acquired using a radiation source () revolving around the associated imaging subject. During the tomographic imaging, an estimated attenuation of radiation is determined for an upcoming position or angular bin () of the revolving radiation source based on attenuations determined at previously acquired positions or angular bins () 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.
System And Method For Disease Diagnosis From Patient Structural Deviation Data
Saad Ahmed Sirohey - Pewaukee WI, US Gopal B. Avinash - Menomonee Falls WI, US Fausto J. Espinal - Waukesha WI, US Zhongmin Lin - New Berlin WI, US Ananth Mohan - Waukesha WI, US Tamanna Bembenek - Naperville IL, US
Assignee:
General Electric Company - Schenectady NY
International Classification:
G06Q 10/00
US Classification:
705 2, 705 3
Abstract:
A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.
System And Method For Mapping Structural And Functional Deviations In An Anatomical Region
Saad Ahmed Sirohey - Pewaukee WI, US Gopal B. Avinash - Menomonee Falls WI, US Fausto J. Espinal - Waukesha WI, US Zhongmin Lin - New Berlin WI, US Ananth Mohan - Waukesha WI, US
Assignee:
General Electric Company - Schenectady NY
International Classification:
G06Q 10/00 A61B 5/05 G06K 9/00 H04N 15/00
US Classification:
705 2, 600407, 382132, 382154, 348 47
Abstract:
A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.