Ge Precision Healthcare LLC

Justin Wright

Amanda Black

Damien Marechal

Chet Larrow

Jerome F Knoplioch

Sean O'Connor

Herve Monochoix

Ravi Soni

James Gualtieri

Sean P OConnor

Kristin Anderson

Herve Monchoix

The current disclosure provides methods and systems for visualizing, comparing, and navigating through, labeled image sequences. In one example, a degree of variation between a plurality of labels for an image in a sequence of images may be encoded as a comparison metric, and the comparison metric for each image may be graphed as a function of image position in the sequence of images, thereby providing a contextually rich view of label variation as a function of progression through the sequence of images. Further, the encoded variation of image labels may be used to automatically flag inconsistently labeled images, wherein the flagged images may be highlighted in a graphical user interface presented to a user, pruned from a training dataset, or a loss associated with the flagged image may be scaled based on the encoded variation during training of a machine learning model.

System and methods for visualizing variations in labeled image sequences for development of machine learning models

Various methods and systems are provided for suggesting annotation shapes to be applied to a medical image. In one example, a method includes outputting, for display on a display device, a set of annotation icons from an icon library based on a current image displayed on the display device and displaying an annotation on the current image in response to selection of an annotation icon from the set. The method further includes automatically adjusting the annotation to a corresponding anatomical feature in the current image and saving the current image with the annotation.

Methods and systems for a medical image annotation tool

Growing community of inventors

San Ramon, CA, United States of America

Justin Wright