Systems and methods for a PET image reconstruction device
AssigneeNeusoft Medical Systems Co., Ltd.
InventorsYunda Li, Zhipeng Sun, Shaolian Liu
Life of this patent
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Abstract
Methods, devices and apparatus for reconstructing a PET image are provided. According to an example of the method, a PET initial image may be reconstructed from PET data obtained by scanning on a target object with a PET device, and an MRI image may be reconstructed from MRI data obtained by scanning on the target object with a MRI device, a fusion image retaining only a boundary of the target object is generated based on the PET initial image and the MRI image, and a PET reconstructed image is obtained by combining the PET initial image with the fusion image, where the definition of the boundary of the target object in the PET reconstructed image is higher than that in the PET initial image.
Claims16
A method of reconstructing a Positron Emission Tomography (PET) image, comprising:
- obtaining PET data by scanning a target object with a PET device,
- obtaining Magnetic Resonance Imaging (MRI) data by scanning the target object with an MRI device,
- reconstructing a PET initial image and an MRI image from the PET data and the MRI data respectively;
- generating a fusion image retaining only a boundary of the target object based on the PET initial image and the MRI image, wherein definition of the boundary of the target object in the fusion image is higher than that in the PET initial image;
- and
- obtaining a PET reconstructed image by combining the PET initial image with the fusion image, wherein the definition of the boundary of the target object in the PET reconstructed image is higher than that in the PET initial image;
- wherein obtaining the PET reconstructed image comprising:
- decomposing the PET initial image into N first initial sub-images with different frequency characteristics by performing wavelet transform, wherein N=2″, and n is an integer greater than or equal to 1;
- decomposing the fusion image into N second initial sub-images with different frequency characteristics by performing wavelet transform;
- generating a target sub-image by performing weighted stacking pixel values of every two pixels at same positions in each of the first initial sub-images and one of the second initial sub-images which has same frequency characteristic as the first initial sub-image;
- and
- obtaining the PET reconstructed image by performing wavelet inverse transform to the N target sub-images.
A PET image reconstruction device comprising a processor, wherein by reading and executing machine executable instructions corresponding to a control logic for PET imaging and stored on a machine readable storage medium, the processor is caused to:
- obtain PET data by scanning a target object with a PET device, and
- reconstruct a PET initial image from the PET data;
- obtain an MRI image for the target object generated by an MRI device;
- generate a fusion image retaining only a boundary of the target object based on the PET initial image and the MRI image, wherein definition of the boundary of the target object in the fusion image is higher than that in the PET initial image;
- and
- obtain a PET reconstructed image by combining the PET initial image with the fusion image, wherein the definition of the boundary of the target object in the PET reconstructed image is higher than that in the PET initial image;
- wherein when obtaining the PET reconstructed image, the machine executable instructions cause the processor to:
- decompose the PET initial image into N first initial sub-images with different frequency characteristics by performing wavelet transform, wherein N=2″, and n is an integer greater than or equal to 1;
- decompose the fusion image into N second initial sub-images with different frequency characteristics by performing wavelet transform;
- generate a target sub-image by performing weighted stacking pixel values of every two pixels at same positions in each of the first initial sub-images and one of the second initial sub-images which has same frequency characteristic as the first initial sub-image;
- and
- obtain the PET reconstructed image by performing wavelet inverse transform to the N target sub-images.
Dependencies are inferred from the claim text.