Patent · US Active

Trained generative network for lung segmentation in medical imaging

US10607114B2 · kind B2 · utility

1Cited by

0References

17Claims

0Family size

Assignee

Siemens Healthcare Limited · DE

Inventors

Carol L. Novak · Newtown, US
Benjamin L. Odry · West New York, US
Atilla Peter Kiraly · Plainsboro, US
Jiancong Wang · Chengdu, CN

Key dates

Filing date	Jan 16, 2018
Grant date	Mar 31, 2020
Priority date	—
Expiry date	May 25, 2038

Classification

Technology area (CPC G)Physics
CPC primaryG06V2201/031
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A generative network is used for lung lobe segmentation or lung fissure localization, or for training a machine network for lobar segmentation or localization. For segmentation, deep learning is used to better deal with a sparse sampling of training data. To increase the amount of training data available, an image-to-image or generative network localizes fissures in at least some of the samples. The deep-learnt network, fissure localization, or other segmentation may benefit from generative localization of fissures.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.