Heartflow, Inc.

Peter Kersten Petersen

Leo John Grady

Michiel Schaap

David Lesage

Sethuraman Sankaran

Christopher K Zarins

Ying Bai

Edward Karl Hahn, Iii

Systems and methods are disclosed for performing probabilistic segmentation in anatomical image analysis, using a computer system. One method includes receiving a plurality of images of an anatomical structure; receiving one or more geometric labels of the anatomical structure; generating a parametrized representation of the anatomical structure based on the one or more geometric labels and the received plurality of images; mapping a region of the parameterized representation to a geometric parameter of the anatomical structure; receiving an image of a patient's anatomy; and generating a probability distribution for a patient-specific segmentation boundary of the patient's anatomy, based on the mapping of the region of the parameterized representation of the anatomical structure to the geometric parameter of the anatomical structure.

Systems and methods for probabilistic segmentation in anatomical image processing

Systems and methods are disclosed for anatomic structure segmentation in image analysis, using a computer system. One method includes: receiving an annotation and a plurality of keypoints for an anatomic structure in one or more images; computing distances from the plurality of keypoints to a boundary of the anatomic structure; training a model, using data in the one or more images and the computed distances, for predicting a boundary in the anatomic structure in an image of a patient's anatomy; receiving the image of the patient's anatomy including the anatomic structure; estimating a segmentation boundary in the anatomic structure in the image of the patient's anatomy; and predicting, using the trained model, a boundary location in the anatomic structure in the image of the patient's anatomy by generating a regression of distances from keypoints in the anatomic structure in the image of the patient's anatomy to the estimated boundary.

Systems and methods for anatomic structure segmentation in image analysis

Systems and methods are disclosed for performing probabilistic segmentation in anatomical image analysis, using a computer system. One method includes receiving a plurality of images of an anatomical structure; receiving one or more geometric labels of the anatomical structure; generating a parameterized representation of the anatomical structure based on the one or more geometric labels and the received plurality of images; mapping a region of the parameterized representation to a geometric parameter of the anatomical structure; receiving an image of a patient's anatomy; and generating a probability distribution for a patient-specific segmentation boundary of the patient's anatomy, based on the mapping of the region of the parameterized representation of the anatomical structure to the geometric parameter of the anatomical structure.

Systems and methods for probablistic segmentation in anatomical image processing

Systems and methods are disclosed for associating medical images with a patient. One method includes: receiving two or more medical images of patient anatomy in an electronic storage medium; generating an anatomical model for each of the received medical images; comparing the generated anatomical models; determining a score assessing the likelihood that the two or more medical images belong to the same patient, using the comparison of the generated anatomical models; and outputting the score to an electronic storage medium or display.

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Palo Alto, CA, United States of America

Peter Kersten Petersen