Invention Grant
- Patent Title: Posterior image sampling using statistical learning model
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Application No.: US16189480Application Date: 2018-11-13
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Publication No.: US10672153B2Publication Date: 2020-06-02
- Inventor: Jonas Anders Adler , Ozan Öktem
- Applicant: Elekta AB (publ)
- Applicant Address: SE Stockholm
- Assignee: Elekta AB (publ)
- Current Assignee: Elekta AB (publ)
- Current Assignee Address: SE Stockholm
- Agency: Schwegman Lundberg & Woessner, P.A.
- Agent Sanjay Agrawal
- Main IPC: G06T11/00
- IPC: G06T11/00 ; G06T7/10

Abstract:
Image reconstruction can include using a statistical or machine learning, MAP estimator, or other reconstruction technique to produce a reconstructed image from acquired imaging data. A Conditional Generative Adversarial Network (CGAN) technique can be used to train a Generator, using a Discriminator, to generate posterior distribution sampled images that can be displayed or further processed such as to help provide uncertainty information about a mean reconstruction image. Such uncertainty information can be useful to help understand or even visually modify the mean reconstruction image. Similar techniques can be used in a segmentation use-case, instead of a reconstruction use case. The uncertainty information can also be useful for other post-processing techniques.
Public/Granted literature
- US20190325620A1 POSTERIOR IMAGE SAMPLING USING STATISTICAL LEARNING MODEL Public/Granted day:2019-10-24
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06T | 一般的图像数据处理或产生 |
G06T11/00 | 2D〔二维〕图像的生成 |