A new algorithm using the geometric active contour model with the fusion of color and intensity priors to segment medical images is presented in this paper. The prior knowledge used here are firstly defined in different color spaces and represented as thresholds searched by the genetic algorithm. Then the prior knowledge is merged into active contour model with its contour evolution by the level set technique. The experiments on clinical marrow images and mammograms have successfully demonstrated its superiority of the proposed algorithm over the existing active contour models which deal with image gradient information.
Algorithms ; Artificial Intelligence ; Color ; Image Enhancement ; Image Interpretation, Computer-Assisted

To get precise and complete details, the contrast in different images is needed in medical diagnosis and computer assisted treatment. The image registration is the basis of contrast, but the regular rigid registration does not satisfy the clinic requirements. A non-rigid medical image registration method based on mutual information and thin-plate spline was present. Firstly, registering two images globally based on mutual information; secondly, dividing reference image and global-registered image into blocks and registering them; then getting the thin-plate spline transformation according to the shift of blocks' center; finally, applying the transformation to the global-registered image. The results show that the method is more precise than the global rigid registration based on mutual information and it reduces the complexity of getting control points and satisfy the clinic requirements better by getting control points of the thin-plate transformation automatically.
Algorithms ; Image Enhancement ; methods ; Image Interpretation, Computer-Assisted ; methods

At present, ray-casting algorithm is the most widely used algorithm in the field of medical image visualization, and it can achieve the best image quality. Due to large amounts of computation like sampling, gradient, lighting and blending calculation, the cost of ray-casting algorithm is very large. The characteristic of Streaming single instruction multiple datum extensions (SSE) instruction--supporting vector computation--can satisfy the property of ray-casting algorithm well. Therefore, in this paper, we improved the implementation efficient significantly by vectorization of gradient, lighting and blending calculation, and still achieved a high quality image at the same time.
Algorithms ; Humans ; Image Interpretation, Computer-Assisted ; methods ; Image Processing, Computer-Assisted ; methods ; Pattern Recognition, Automated ; methods

This paper analyzes the present situation and focuses of medical image fusion and especially places emphasis on the developing trend of intelligent image fusion and comachine image fusion technologies.
Diagnostic Imaging ; methods ; Image Interpretation, Computer-Assisted ; Image Processing, Computer-Assisted ; Medical Informatics Applications

The object of this study was to work at accurate axis registration and interpolation methods for multi-dimension reconstruction of rotary scanning ultrasonic medical images. At first, time-field curves of the images' axes were analyzed according to their characteristic points and the axial direction registration was realized. Similar matrix was used to find registration pixels line near the axes of two images. Auto-correlation function and Fourier spectrum were used to evaluate the effects of axes registration. Second, an interpolation method was studied for the special space distribution of rotary scanning images. Results of experiments indicate that the axes registration and interpolation methods were suitable to rotary scanning medical images. The quality of reconstruction can be greatly improved by registration-based interpolation methods.
Algorithms ; Echocardiography ; methods ; Humans ; Image Interpretation, Computer-Assisted ; methods ; Image Processing, Computer-Assisted ; methods

When MR image's area is too small compared with the whole picture, the use of the current auto-window algorithms usually gets poor clarity and contrast. In order to address this problem, an improved auto-window algorithm is proposed in this paper and can solve the problem effectively and get clear and rich layers of MR images quickly and easily.
Algorithms ; Image Interpretation, Computer-Assisted ; methods ; Magnetic Resonance Imaging ; methods

This paper presents an approach to GPU-based ray-casting of a shader model 3.0 compatible graphics card. In addition, a software toolkit is designed using the proposed algorithm to make the full benefit of GPU by extending VTK. Experimental results suggest that remarkable speedups are observed using GPU-based algorithm, and high-quality renderings can be achieved at interactive framerates above 60 fps. The toolkit designed provides a high level of usability and extendibility.
Algorithms ; Image Interpretation, Computer-Assisted ; methods ; Software Design

Ultrasound image has a lot of speckle noise, which brings great difficulties to the feature extraction, recognition and analysis. Especially in the edge extraction, the conventional extraction algorithms are difficult to achieve the desired results because of the speckle noise. To solve this problem, an algorithm based on the anisotropic diffusion equation is presented. The new algorithm combines the robust estimation and considers the characteristic of the speckle noise, so it can suppress the speckle noise effectively and be more robust, thus the edge details of the ultrasound image can be preserved even enhanced, which can provide effective safeguard for the following edge extraction. Furthermore, the paper proposes a new method to compute speckle scale coefficients automatically, which reduces the influence of the human beings, and enhances the stability of the algorithm.
Algorithms ; Artifacts ; Image Interpretation, Computer-Assisted ; Ultrasonography ; methods

A method of medical image segmentation based on support vector machine (SVM) for density estimation is presented. We used this estimator to construct a prior model of the image intensity and curvature profile of the structure from training images. When segmenting a novel image similar to the training images, the technique of narrow level set method is used. The higher dimensional surface evolution metric is defined by the prior model instead of by energy minimization function. This method offers several advantages. First, SVM for density estimation is consistent and its solution is sparse. Second, compared to the traditional level set methods, this method incorporates shape information on the object to be segmented into the segmentation process. Segmentation results are demonstrated on synthetic images, MR images and ultrasonic images.
Humans ; Image Interpretation, Computer-Assisted ; methods ; Magnetic Resonance Imaging

There are many kinds of artifacts in image series of functional MRI, such as head motion artifacts, physiological motion artifacts, blood flow artifacts, ghost artifacts and susceptibility artifacts. These artifacts which are unassociated with the neural activities, have so severe affects on the analysis of functional MRI data that they not only reduce the sensibility and reliability of functional MRI, but also make the detecting, locating and visualizing of the functional active regions more complicated. The mechanism and the effect of artifacts in functional MRI are discussed here, the methods of correcting artifacts are reviewed, and research prospects are discussed too.
Artifacts ; Image Interpretation, Computer-Assisted ; Magnetic Resonance Imaging ; methods