Publication

Ultrasound imaging with beamforming from data that are enhanced by a neural network in the signal domain

Jean-Philippe Thiran
2026

Abstract

[0001] To obtain a data-structure that is characteristic of a physical object, a computer receives (413) sensor-data ({{y}}|↓) from a sensor-array. the received sensor-data ({{y}}|↓) is - in spatial and temporal data arrangement - a sub-set of sensor-data of a reference sensor-array. the computer uses a neural network to enhance (433) the received sensor-data to enhanced sensor-data so that - in spatial and temporal data arrangement - the enhanced sensor-data correspond to the sensor-data of the reference sensor-array. an imaging module beamforms (453) the enhanced sensor-data to the data-structure. the neural network has been trained (402) to obtain network weights, with sensor-data from the ultrasound transducer elements of the reference sensor-array.

Official source

https://infoscience.epfl.ch/entities/publication/e809fd3e-667b-4be0-b053-fd106690104f

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Jean-Philippe Thiran
2026

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/e809fd3e-667b-4be0-b053-fd106690104f

About this result

Related concepts (32)

Computer

A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations (computation) automatically. Modern digital electronic computers can perform generic sets of operations known as programs. These programs enable computers to perform a wide range of tasks. A computer system is a nominally complete computer that includes the hardware, operating system (main software), and peripheral equipment needed and used for full operation.

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Recurrent neural network

A recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.

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Ultrasound imaging with beamforming from data that are enhanced by a neural network in the signal domain

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