Ultrasound image matching using genetic algorithms.

Image compounding reduces the artifacts inherent in ultrasound imaging, but accurate matching of images for compounding depends on their accurate placement in the compound image plane. A method is presented to reduce displacement errors during compounding of ultrasound B-scans of a normal human shank. A genetic algorithm was used to place matching B-scans in the compound image. The method was tested on a phantom and was shown to reduce, but not eliminate, mismatches due to the displacement of B-scans from their original position in the compound image plane. The results can be extended to applications in lower-limb prosthetics, where ultrasound imaging can be used to visualise the internal geometry of amputees' residual limbs.

Automatic segmentation of magnetic resonance images of the trans-femoral residual limb.

An automatic algorithm for the extraction of the skin and bone boundaries from axial magnetic resonance images of the residual limb of trans-femoral amputees is presented. The method makes use of K-means clustering and mathematical morphology. Statistical analysis of the results indicates that the computer-generated boundaries compare favourably to those drawn by human observers. The boundaries may be used in biomechanical modelling of the interaction between the residual limb and the prosthetic socket. The limb/socket interface determines the quality of prosthetic fit, therefore knowledge of this interface is important for the improvement of socket design in order to achieve patient comfort and mobility.

ANN compression of morphologically similar ECG complexes.

A compression algorithm for electrocardiogram signals is presented, based on an auto-associative neural network. Issues of weight and activation coding are considered, and compression performances of various network sizes are compared. A unique feature is the performance improvement achieved using DC level removal. A comparison with existing techniques is provided.