Three-dimensional modeling and assessment of cardiac tissue
A system for patient cardiac imaging and tissue modeling. The system includes a patient imaging device that can acquire patient cardiac imaging data. A processor is configured to receive the cardiac imaging data. A user interface and display allow a user to interact with the cardiac imaging data. The processor includes fat identification software conducting operations to interact with a trained learning network to identify fat tissue in the cardiac imaging data and to map fat tissue onto a three-dimensional model of the heart. A preferred system uses an ultrasound imaging device as the patient imaging device. Another preferred system uses an MRI or CT image device as the patient imaging device.
1. A system for patient cardiac imaging and tissue modeling, comprising:
an echocardiograph configured to acquire patient 3D cardiac imaging data with raw 2D spectral cardiac imaging data;
a processor to receive the patient 3D cardiac imaging data with raw 2D spectral cardiac imaging data; and
software run by the processor to provide the patient 3D cardiac imaging data and the raw 2D spectral cardiac imaging data to a trained learning network to identify a left ventricle, a right ventricle and fat and generate a 3D patient cardiac image labelled with fat; and
a user interface and display to interact with the patient 3D cardiac image;
wherein the trained learning network was trained by obtaining training magnetic resonance imaging 3D cardiac imaging data and training echocardiograph 3D cardiac imaging data with training raw 2D spectral cardiac imaging data by using deep learning to find left and right ventricles in the training magnetic resonance imaging 3D cardiac imaging data and training echocardiograph 3D cardiac imaging data, by fitting a training 3D model to a labeled image volume including fat labels, and by registering the training raw 2D spectral cardiac imaging data with the training 3D model.
2. The system of claim 1 , comprising analysis software that predicts coronary disease based upon the 3D patient cardiac image labelled with fat based upon fat tissue mapped in locations near coronary arteries.
3. The system of claim 2 , wherein the analysis software compares the fat tissue mapped in locations near coronary arteries to a database of coronary plaque obtained by intravascular ultrasound.
4. The system of claim 1 , wherein the registering the training raw 2D spectral cardiac imaging data with the training 3D model comprises using segmented structures in the raw 2D spectral cardiac imaging data and aligning contours from the patient 3D cardiac imaging data with the surfaces of the training 3D model.