Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Nonlinear adaptive filters for speckle suppression in ultrasonic images
Signal Processing
Adaptive Nonlocal Filtering: A Fast Alternative to Anisotropic Diffusion for Image Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing: PIKS Inside
Digital Image Processing: PIKS Inside
Anisotropic filtering for model-based segmentation of 4D cylindrical echocardiographic images
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Multiscale Nonlinear Diffusion and Shock Filter for Ultrasound Image Enhancement
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A comparison of selection schemes used in evolutionary algorithms
Evolutionary Computation
Speckle reducing anisotropic diffusion
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Inter-frame Enhancement of Ultrasound Images Using Optical Flow
IVIC '09 Proceedings of the 1st International Visual Informatics Conference on Visual Informatics: Bridging Research and Practice
Hi-index | 0.00 |
Objective: So far there is no ideal speckle reduction filtering technique that is capable of enhancing and reducing the level of noise in medical ultrasound (US) images, while efficiently responding to medical experts' validation criteria which quite often include a subjective component. This paper presents an interactive tool called evolutionary speckle reducing anisotropic diffusion filter (EVOSRAD) that performs adaptive speckle filtering on ultrasound B-mode still images. The medical expert runs the algorithm interactively, having a permanent control over the output, and guiding the filtering process towards obtaining enhanced images that agree to his/her subjective quality criteria. Methods and material: We employ an interactive evolutionary algorithm (IGA) to adapt on-line the parameters of a speckle reducing anisotropic diffusion (SRAD) filter. For a given input US image, the algorithm evolves the parameters of the SRAD filter according to subjective criteria of the medical expert who runs the interactive algorithm. The method and its validation are applied to a test bed comprising both real and simulated obstetrics and gynecology (OB/GYN) ultrasound images. Results: The potential of the method is analyzed in comparison to other speckle reduction filters: the original SRAD filter, the anisotropic diffusion, offset and median filters. Results obtained show the good potential of the method on several classes of OB/GYN ultrasound images, as well as on a synthetic image simulating a real fetal US image. Quality criteria for the evaluation and validation of the method include subjective scoring given by the medical expert who runs the interactive method, as well as objective global and local quality criteria. Conclusions: The method presented allows the medical expert to design its own filters according to the degree of medical expertise as well as to particular and often subjective assessment criteria. A filter is designed for a given class of ultrasound images and for a given medical expert who will later use the respective filter in clinical practice. The process of designing a filter is simple and employs an interactive visualization and scoring stage that does not require image processing knowledge. Results show that filters tailored using the presented method achieve better quality scores than other more generic speckle filtering techniques.