Abstract: For shape determination of cardiac anatomy with a medical imager, irregularities in motion, poor image quality, and misalignment of imaging planes are counteracted by a process relying on alignment of contours in combination with selection and fitting of a motion model. Contours are extracted from 2D images and aligned for each frame, which is extracted from the sequence of 2D images. The alignment may use a translation for each frame and rotation across frames for improved performance. A motion model is fit to the aligned contours and tested. If insufficient (greater than threshold difference), other motion models are aligned and tested. Motion models may be created on demand for improved performance. If sufficient, the shape of the heart structure is determined from the fit model.

Abstract: A neural network system for retraining operational neural networks using a synthetic data set generated by a synthetic data generator neural network is provided. The synthetic data generator network comprises an input layer for receiving an input data set; an output layer for outputting the synthetic data set; and a loss function for receiving from each operational network a value of a medical metric. The operational networks each comprise an input layer for receiving the synthetic data set; and an output layer for outputting the value of the medical metric. The synthetic data generator network is trained for generating the synthetic data set based on the loss function comprising a difference of the values of the medical metric. Each operational network is retrained using the synthetic data set.

Abstract: Methods for computed tomography data-based cycle estimation and four-dimensional reconstruction are provided. A gated reconstruction is derived from CT data acquired without gating using an added artificial trigger. The resulting images for different slices are used to determine local or slice variations over time. The local variations over time for the various slices are combined to create a respiratory cycle signal. This respiratory cycle signal is used to bin the images for different phases, allowing four-dimensional CT reconstruction.

Abstract: Methods for computed tomography data-based cycle estimation and four-dimensional reconstruction are provided. A gated reconstruction is derived from CT data acquired without gating using an added artificial trigger. The resulting images for different slices are used to determine local or slice variations over time. The local variations over time for the various slices are combined to create a respiratory cycle signal. This respiratory cycle signal is used to bin the images for different phases, allowing four-dimensional CT reconstruction.