Koninklijke Philips Corporation N.v.

Shiyu Xu

Chuanyong Bai

Hao Dang

Hui Wang

Hao Lai

Douglas B McKnight

Sheng Lu

Jens Wiegert

Yang-Ming Zhu

Peter Prinsen

Ravindra Mohan Manjeshwar

Douglas Mcknight

Yang-ming Zhu

A computer tomography scanner () includes a radiation source () configured to emit x-ray radiation, a detector array () configured to detect x-ray radiation and generate a signal indicative thereof, and a reconstructor () configured to reconstruct the signal and generate sequential spares time line perfusion volumetric image data. The computer tomography scanner further includes a processor () configured to process the sequential spares time line perfusion volumetric image data using a trained neural network of a perfusion data enhancing module () to produce sequential dense time line perfusion volumetric image data.

Low radiation dose computed tomography perfusion (CTP) with improved quantitative analysis

A non-spectral computed tomography scanner includes a radiation source configured to emit x-ray radiation, a detector array configured to detect x-ray radiation and generate non-spectral data, and a memory configured to store a spectral image module that includes computer executable instructions including a neural network trained to produce spectral volumetric image data. The neural network is trained with training spectral volumetric image data and training non-spectral data. The non-spectral computed tomography scanner further includes a processor configured to process the non-spectral data with the trained neural network to produce spectral volumetric image data.

Non-spectral computed tomography (CT) scanner configured to generate spectral volumetric image data

A spectral computed tomography imaging system () includes a radiation source () configured to emit x-ray radiation and a detector array () configured to detect x-ray radiation and generate spectral data. The spectral imaging system further includes a memory () configured to store a virtual non-contrast image enhancing module () that includes computer executable instructions including a neural network trained to produce image quality enhanced virtual non-contrast images. The neural network is trained with training spectral data and training non-contrast-enhanced images generated from a non-contrast-enhanced scan. The spectral imaging system further includes a processor () configured to process the spectral data with the trained neural network to produce the image quality enhanced virtual non-contrast images.

Image quality improved virtual non-contrast images generated by a spectral computed tomography (CT) scanner

An imaging system includes a computed tomography (CT) imaging device () (optionally a spectral CT), an electronic processor (), and a non-transitory storage medium () storing a neural network () trained on simulated imaging data () generated by Monte Carlo simulation () including simulation of at least one scattering mechanism () to convert CT imaging data to a scatter estimate in projection space or to convert an uncorrected reconstructed CT image to a scatter estimate in image space. The storage medium further stores instructions readable and executable by the electronic processor to reconstruct CT imaging data () acquired by the CT imaging device to generate a scatter-corrected reconstructed CT image (). This includes generating a scatter estimate () by applying the neural network to the acquired CT imaging data or to an uncorrected CT image () reconstructed from the acquired CT imaging data.

Deep learning based scatter correction

A non-spectral computed tomography scanner () includes a radiation source () configured to emit x-ray radiation, a detector array () configured to detect x-ray radiation and generate non-spectral data, and a memory () configured to store a spectral image module () that includes computer executable instructions including a neural network trained to produce spectral volumetric image data. The neural network is trained with training spectral volumetric image data and training non-spectral data. The non-spectral computed tomography scanner further includes a processor () configured to process the non-spectral data with the trained neural network to produce spectral volumetric image data.

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Mayfield Heights, OH, United States of America

Shiyu Xu