Home List of Titles Ultrasound image reconstruction by two-dimensional blind total variation deconvolution
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/194074
|Download PDF (Published version) (Adobe Acrobat PDF, 562 KB)|
- Ultrasound image reconstruction by two-dimensional blind total variation deconvolution
- Huang, Zheng; Zhang, Jingxin; Zhang, Cishen
- The main inherent property of medical ultrasound imaging is speckle noise which generally obscures and reduces the diagnostic image resolution and contrast. Consequently, the substantial improvement of ultrasound images is an important prerequisite, whenever ultrasound is used as one of the most utilized diagnostic modalities. The problem of reconstruction of ultrasound images by means of blind deconvolution has long been recognized as a prerequisite in ultrasound imaging processing in the recent decades. Recently, the Total Variation (TV) regularization method has become extremely effective approach for image reconstruction, especially for restoring edges of the blurring image. In this paper, we present a new blind iterative TV deconvolution algorithm for reconstructing ultrasound images from blurry and noisy observations. First, it proposes the initial estimation of the point-spread function (PSF) based on a generalization of two-dimensional homomorphic filtering in cepstrum domain. It is demonstrated that the initial PSF can be effectively estimated by applying a proper smoothing low-pass filtering in cepstrum domain. Second, it introduces a novel blind iterative TV deconvolution which is derived from an alternating minimization algorithm. Fast Fourier Transform (FFT) is used in the pre-iteration computation. The innovative blind deconvolution is based on either concurrent or successive estimation of the PSF function and the image of interest. The iterative scheme is devised to recover the image and simultaneously identify the PSF function. The estimated PSF and restored image will be close to real values in the subsequent iterative deconvolution. Final, tests on phantom and clinical images have proven our novel blind iterative TV deconvolution gives more positive results of higher spatial resolution and better defined tissue structures than other deconvolution methods.
- Publication type
- Conference paper
- Proceedings of the IEEE International Conference on Control and Automation (ICCA 2009), Christchurch, New Zealand, 09-11 December 2009, pp. 1801-1806
- Publication year
- Alternating minimisation algorithms; Blind deconvolution; Cepstrum; Clinical images; Computerised tomography; Convolution; Deconvolution algorithm; Deconvolution method; Diagnostic images; Diagnostic modality; Edge detection; Fast Fourier transforms; Homomorphic filtering; Image reconstruction; Image resolution; Initial estimation; Iteration computation; Iterative deconvolution; Iterative schemes; Low-pass filtering; Medical ultrasound imaging; Noisy observations; Optical transfer function; Point-spread functions; Spatial resolution; Speckle noise; Tissue structure; Total variation regularisation; Two dimensional; Ultrasonic transmission; Ultrasound images
- 9781424447060, 1424447062
- Publisher URL
- Copyright © 2009 IEEE. The published version of the paper is reproduced here in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
- Full text
- Peer reviewed