Patent · US Active

Material segmentation in image volumes

US10438350B2 · kind B2 · utility

6Cited by
5References
14Claims
0Family size

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Key dates

Filing dateJun 27, 2017
Grant dateOct 8, 2019
Priority date
Expiry dateNov 7, 2037

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06T2207/30008
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

The present approach relates, in some aspects, to a multi-level and a multi-channel frame work for segmentation using model-based or “shallow” classification (i.e. learning processes such as linear regression, clustering, support vector machines, and so forth) followed by deep learning. This framework starts with a very low resolution version of the multi-channel data and constructs an shallow classifier with simple features to generate a coarser level tissue mask that in turn is used to crop patches from the high-resolution volume. The cropped volume is then processed using the trained convolution network to perform a deep learning based segmentation within the slices.

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