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Compressive Sensing with Optical Transmission Matrix

A technology of compressed sensing and optical transmission, applied in 3D image processing, image enhancement, instruments, etc., can solve the problems of processing and storage tasks that are difficult to handle, and limit the efficient use of optical transmission matrices

Active Publication Date: 2020-08-21
SIEMENS HEALTHCARE GMBH
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Problems solved by technology

Such a large size makes tasks such as processing and storage intractable from a computational perspective
This limits the ability to efficiently utilize light transport matrices in applications such as medical imaging applications

Method used

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  • Compressive Sensing with Optical Transmission Matrix
  • Compressive Sensing with Optical Transmission Matrix
  • Compressive Sensing with Optical Transmission Matrix

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Embodiment Construction

[0018] The following disclosure describes the invention in terms of several embodiments relating to methods, systems and apparatus related to compressive sensing (CS) of optical transmission matrices. Optical transfer matrices are very large matrices. Its size is defined by all possible combinations of points and their relationships. But by virtue of CS, and in some embodiments by virtue of other fundamental observations in rendering (ie, rapid drop-off of visibility between points, sparsity of visibility signal frequency), the size of the matrix can be significantly reduced. Therefore, CS can be used to reconstruct the light transport matrix from a tiny amount of samples. After rebuilding this matrix, any given two points and their visibility to each other can be known in advance. Therefore, there will be no need to explore the space. Only large contributing samples can be detected without exploration and noise-free images can be generated.

[0019] figure 1 An illustrat...

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Abstract

Compressed sensing of optical transmission matrices. A computer-implemented method for performing compressed sensing of a light transport matrix, the method comprising receiving a 3D dataset comprising image volume data, and randomly selecting a plurality of points on a spatial curve traversing the 3D dataset. Compute a light transmission matrix that includes multiple transmittance values. Each light transmittance value corresponds to light transmittance between pairs of dots included in the plurality of dots. The optimization problem is solved to determine a plurality of sparse coefficients that reproduce the light transport matrix when multiplied by a dictionary of predetermined basis vectors. Once determined, the sparse coefficients are stored on a computer readable medium.

Description

technical field [0001] The present invention generally relates to methods, systems and apparatus for using compressive sensing techniques in the calculation of optical transfer matrices. The techniques described herein may be applied, for example, to 3D medical imaging applications. Background technique [0002] Generating distinct and physically plausible images is an important task for users to gain a deeper understanding of data. In order for a computer to generate such images, light-material interactions must be considered. Those interactions are calculated through a mathematical and physical basis set by light transport algorithms. Since it is impossible to calculate all interactions, a different mathematical approach is used from conventional techniques. [0003] A popular method for calculating light interactions is to use Monte Carlo (MC) statistical methods. Complex phenomena can be computed with MC methods, but artifacts of these algorithms appear as noise in t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T15/50G06T15/08G06T7/136G06T1/00G06T1/20
CPCH03M7/3062G06T15/06G06T15/08G06T2210/41G06T15/506G06T7/136G06T2207/20G06T1/0007G06T2207/10028G06T1/20
Inventor A.比尔吉利
Owner SIEMENS HEALTHCARE GMBH
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