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Karen Drukker Phones & Addresses

  • Beecher, IL
  • 304 Milburn Ave, Crete, IL 60417 (708) 672-4772
  • Mundelein, IL
  • 1337 Fargo Ave, Chicago, IL 60626 (773) 761-8724
  • South Bend, IN

Publications

Us Patents

Automated Method And System For The Detection Of Abnormalities In Sonographic Images

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US Patent:
2003012, Jul 3, 2003
Filed:
Apr 22, 2002
Appl. No.:
10/126523
Inventors:
Karen Drukker - Chicago IL,
Maryellen Giger - Elmhurst IL,
Karla Horsch - Lombard IL,
Carl Vyborny - Riverside IL,
Assignee:
The University of Chicago - Chicago IL
International Classification:
A61B008/00
US Classification:
600/437000
Abstract:
A method of detecting a candidate abnormality in a sonographic medical image, based on determining a radial gradient index (RGI) at plural pixels, producing an RGI image, thresholding the RGI image, determining a candidate abnormality based on the thresholding step, and locating a center point of the candidate abnormality. The candidate abnormality may be classified by segmenting the candidate abnormality, including determining average radial gradients (ARDs) in the sonographic medical image based on the center point, extracting plural features from the segmented candidate abnormality, and determining a likelihood of the candidate abnormality being an actual abnormality based on the extracted plural features.

Computerized Schemes For Detecting And/Or Diagnosing Lesions On Ultrasound Images Using Analysis Of Lesion Shadows

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US Patent:
2003016, Aug 28, 2003
Filed:
Feb 22, 2002
Appl. No.:
10/079820
Inventors:
Karen Drukker - Chicago IL,
Maryellen Giger - Elmhurst IL,
Assignee:
The University of Chicago - Chicago IL
International Classification:
G06K009/00
US Classification:
382/128000
Abstract:
Computerized detection and diagnostic schemes for sonographic images combine the benefits of computerized machine detection with the acquisition of non-radiographic medical images of special use for the screening of high risk, young patients who do not want the effects of ionizing characteristic of mammography. The lesion schemes employ computer-assisted interpretation of medical sonographic images, and output potential lesion sites and/or diagnosis of those lesions. More specifically, an embodiment of the computerized detection scheme involves convoluting a sonographic image with a mask of a given ROI (region of interest) size, and calculating a skewness value for each mask location, and assembling the calculated skewness values to form a skewness image. Thresholds are applied to pixels of the skewness image to determine potential shadows. (Ultrasound images show characteristic posterior acoustic behavior for different lesion types: Posterior acoustic shadowing is often observed for malignant lesions and for some benign solid masses, while posterior acoustic enhancement is often seen for cysts.) An embodiment of the diagnostic scheme (classifying a detected lesion as malignant or benign, for example) involves calculating the skewness of a shadow of a detected lesion, and comparing the calculated skewness to a threshold to arrive at a diagnosis. The detection and diagnostic schemes may also involve merging skewness values with other values determined in accordance with other analytic features, to arrive more comprehensive detection and diagnoses. The schemes are computationally efficient, allowing their use in real-time sonography.

Method, System, Software And Medium For Advanced Intelligent Image Analysis And Display Of Medical Images And Information

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US Patent:
2012018, Jul 26, 2012
Filed:
Nov 28, 2011
Appl. No.:
13/305495
Inventors:
Maryellen L. Giger - Elmhurst IL,
Robert Tomek - Chicago IL,
Jeremy Bancroft Brown - Chicago IL,
Andrew Robert Jamieson - Chicago IL,
Li Lan - Hinsdale IL,
Michael R. Chinander - Chicago IL,
Karen Drukker - Crete IL,
Hui Li - Naperville IL,
Neha Bhooshan - Potomac MD,
Gillian Newstead - Chicago IL,
International Classification:
G06K 9/46
US Classification:
382128
Abstract:
Computerized interpretation of medical images for quantitative analysis of multi-modality breast images including analysis of FFDM, 2D/3D ultrasound, MRI, or other breast imaging methods. Real-time characterization of tumors and background tissue, and calculation of image-based biomarkers is provided for breast cancer detection, diagnosis, prognosis, risk assessment, and therapy response. Analysis includes lesion segmentation, and extraction of relevant characteristics (textural/morphological/kinetic features) from lesion-based or voxel-based analyses. Combinations of characteristics in several classification tasks using artificial intelligence is provided. Output in terms of 1D, 2D or 3D distributions in which an unknown case is identified relative to calculations on known or unlabeled cases, which can go through a dimension-reduction technique. Output to 3D shows relationships of the unknown case to a cloud of known or unlabeled cases, in which the cloud demonstrates the structure of the population of patients with and without the disease.
Karen Drukker from Beecher, IL, age ~53 Get Report