Three-dimensional CT imaging method and apparatus

A three-dimensional computer tomography (CT) imaging device based on X-ray dual projection, comprising:

• a storage unit, configured to store a preset three-dimensional volume reconstruction model;
• generating the preset three-dimensional volume reconstruction model comprises:
• obtaining a training data set;
• wherein the training data set is composed of digital radiography (DR) images of reference objects collected circumferentially;
• training to-be-trained three-dimensional volume reconstruction model using DR images with a perpendicular relationship in the training data set to obtain the preset three-dimensional volume reconstruction model;
• an acquisition unit, configured to collect two DR images with a perpendicular relationship for an object to be imaged;
• an obtaining unit, configured to obtain a three-dimensional volume of the object to be imaged corresponding to the two DR images with a perpendicular relationship based on the preset three-dimensional volume reconstruction model;
• and
• an imaging unit, configured to slice the three-dimensional volumes to obtain three-dimensional CT imaging of the object to be imaged,
• wherein, generating the three-dimensional volume reconstruction model stored in the storage unit comprises:
• when obtaining the training data set, obtaining a reference three-dimensional volume and a reference pseudo-sinogram of each of the reference objects based on the training data set;
• wherein the reference pseudo-sinogram is obtained by stacking collected DR images of a same reference object into a three-dimensional matrix according to a collection order, summing sinograms in each layer column by column, and normalizing a sum result;
• dividing the DR images of each reference object in the training data set into a plurality of DR image groups, and each of the DR image groups comprises two DR images with a perpendicular relationship;
• inputting the plurality of DR image groups into the to-be-trained three-dimensional volume reconstruction model, training the to-be-trained three-dimensional volume reconstruction model, and respectively obtaining a training pseudo-sinogram and a training three-dimensional volume;
• calculating a loss value based on the training pseudo-sinogram, the training three-dimensional volume, the reference pseudo-sinogram and the reference three-dimensional volume according to a training sequence;
• terminating the training and obtaining the preset three-dimensional volume reconstruction model in a case that any calculated loss value is less than a target loss value, or the number of training times reaches a target number of times.

An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, the processor is configured to execute the computer program to implement a three-dimensional computed tomography (CT) imaging method based on X-ray dual projection, the method comprises:

• collecting two digital radiography (DR) images with a perpendicular relationship for an object to be imaged;
• obtain a three-dimensional volume of the object to be imaged corresponding to the two DR images with a perpendicular relationship based on a preset three-dimensional volume reconstruction model;
• and
• slicing the three-dimensional volume to obtain three-dimensional CT imaging of the object to be imaged,
• wherein, generating the preset three-dimensional volume reconstruction model comprises:
• obtaining a training data set;
• wherein the training data set is composed of DR images of reference objects collected circumferentially;
• training to-be-trained three-dimensional volume reconstruction model using DR images with a perpendicular relationship in the training data set to obtain the preset three-dimensional volume reconstruction model;
• wherein, when obtaining the training data set, the method further comprises:
• obtaining a reference three-dimensional volume and a reference pseudo-sinogram of each of the reference objects based on the training data set;
• wherein the reference pseudo-sinogram is obtained by stacking collected DR images of a same reference object into a three-dimensional matrix according to a collection order, summing sinograms in each layer column by column, and normalizing a sum result;
• dividing the DR images of each reference object in the training data set into a plurality of DR image groups, and each of the DR image groups comprises two DR images with a perpendicular relationship;
• wherein the training to-be-trained three-dimensional volume reconstruction model using DR images with a perpendicular relationship in the training data set to obtain the preset three-dimensional volume reconstruction model comprises:
• inputting the plurality of DR image groups into the to-be-trained three-dimensional volume reconstruction model, training the to-be-trained three-dimensional volume reconstruction model, and respectively obtaining a training pseudo-sinogram and a training three-dimensional volume;
• calculating a loss value based on the training pseudo-sinogram, the training three-dimensional volume, the reference pseudo-sinogram and the reference three-dimensional volume according to a training order;
• terminating the training and obtaining the preset three-dimensional volume reconstruction model in a case that any calculated loss value is less than a target loss value, or the number of training times reaches a target number of times.