3-D CONVOLUTIONAL NEURAL NETWORKS FOR ORGAN SEGMENTATION IN MEDICAL IMAGES FOR RADIOTHERAPY PLANNING
Number of patents in Portfolio can not be more than 2000
United States of America
Stats
-
N/A
Issued Date -
Jan 13, 2022
app pub date -
Jul 20, 2021
filing date -
Jul 20, 2021
priority date (Note) -
Published
status (Latency Note)
Importance
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for segmenting a medical image. In one aspect, a method comprises: receiving a medical image that is captured using a medical imaging modality and that depicts a region of tissue in a body; and processing the medical image using a segmentation neural network to generate a segmentation output, wherein the segmentation neural network comprises a sequence of multiple encoder blocks, wherein: each encoder block is a residual neural network block comprising one or more two-dimensional convolutional neural network layers, one or more three-dimensional convolutional neural network layers, or both, and each encoder block is configured to process a respective encoder block input to generate a respective encoder block output wherein a spatial resolution of the encoder block output is lower than a spatial resolution of the encoder block input.
First Claim
Family
International Classification(s)
Cited Art Landscape
Patent Citation Ranking
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully