Medical ultrasound images are inherently noised with speckle noise, which may interfere with Computer Aided Diagnostics (CAD) tasks, such as automatic segmentation. A compression and speckle de-noising method is proposed and tested on real clinical breast and fetal ultrasound images. The proposed algorithm is based on the optimization of quantization coefficients when applying Wavelet representation on the image, where the optimization is held such that a pre-defined mathematical fidelity criterion with respect to a desired de-speckled image is obtained. The proposed algorithm yields effective speckle reduction whilst preserving the edges in the images, with a reduced computational burden compared to other existing state-of-the-art methods, such as Optimal Bayesian Non-Local Means (OBNLM). In addition, the images are simultaneously compressed to a target bit-rate. The proposed algorithm is evaluated using both objective mathematical fidelity criteria (such as Structural Similarity and Edge Preserve) as well as subjective radiologists tests. The experimental results demonstrate the ability of the proposed method to achieve de-speckled images with compression ratios of approximately 30:1, whilst obtaining competitive subjective as well as objective fidelity measures with respect to the desired de-speckled images.
Bibliographical noteFunding Information:
This work was supported by the Israeli Ministry of Science and Technology, Israel, and the Ollendorff Minerva Centre of the Andrew and Erna Viterbi Faculty of Electrical Engineering, Technion - Israel Institute of Technology. Minerva is funded through the BMBF. The authors thank Israel Shapiro (M.D. Ph.D.) for providing the medical image data and participating in the subjective evaluation test. The authors also thank Prof. Arie Drugan for participating in the subjective evaluation test
This work was supported by the Israeli Ministry of Science and Technology , Israel, and the Ollendorff Minerva Centre of the Andrew and Erna Viterbi Faculty of Electrical Engineering , Technion - Israel Institute of Technology. Minerva is funded through the BMBF .
- Image compression
- Medical ultrasound images
- Speckle noise
ASJC Scopus subject areas
- Acoustics and Ultrasonics