Interpretable task-specific dimensionality reduction

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United States of America

PATENT NO 12249023
APP PUB NO 20240203039A1
SERIAL NO

18065964

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Abstract

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Systems/techniques that facilitate interpretable task-specific dimensionality-reduction are provided. In various embodiments, a system can access a three-dimensional medical image. In various aspects, the system can generate, via execution of a first deep learning neural network, a voxel-wise weight map corresponding to the three-dimensional medical image and a set of projection vectors corresponding to the three-dimensional medical image. In various instances, the system can generate a set of two-dimensional projection images of the three-dimensional medical image, based on the voxel-wise weight map and the set of projection vectors. In various cases, the first deep learning neural network can be trained in a serial pipeline with a second deep learning neural network that is configured to perform an inferencing task on two-dimensional inputs. This can cause the set of two-dimensional projection images to be tailored to the inferencing task.

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Patent Owner(s)

  • GE PRECISION HEALTHCARE LLC

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  • [Patents Count]

Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Anand, Deepa Bangalore, IN 25 10
Das, Bipul Bengaluru, IN 36 85
Mullick, Rakesh Bangalore, IN 61 705
NT, Sanjay Kumar Hyderabad, IN 2 0
Singhal, Vanika Bangalore, IN 4 0

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