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

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

A filtering algorithm is proposed to deal with the medical ultrasonic image series in video format, which uses the relativity in spatial domain, gray value domain and temporal domain simultaneously. For each frame image, the relativity in spatial domain and gray value domain is utilized to construct the adaptive neighborhood first. Then the spatial weighted and gray value weighted filtering is performed in this neighborhood. Finally, the temporal relativity between the adjacent frames is used to perform the temporal weighted filtering. All the weighted filtering in the three domains uses Gaussian kernel, thus the filtering sensitivity resulting from the threshold selection is reduced, and the stability of the algorithm is enhanced. As it can be seen from the experimental results, the three-domains filtering algorithm can suppress the noise effectively, and the edge details can be reserved well. So it is useful for the feature extraction, recognition and analysis.
Algorithms ; Image Interpretation, Computer-Assisted ; methods ; Ultrasonography ; methods

A method of acquiring radial pulse information from the grid-net area on every pulse image frame is proposed based on the principle of lens imaging and the characteristics of image data. The radial pulse image data are collected by the pulse image sensor. Multi-points out-of-plane displacements of the pulse are acquired by the method. And the membrane surfaces are reconstructed, then the 3D information of the pulse can be observable.
Image Interpretation, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; 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

In this paper is proposed a new method to solve the segmentation of the complicated defocusing urinary sediment image. The main points of the method are: (1) using wavelet transforms and morphology to erase the effect of defocusing and realize the first segmentation, (2) using adaptive threshold processing in accordance to the subimages after wavelet processing, and (3) using 'peel off' algorithm to deal with the overlapped cells' segmentations. The experimental results showed that this method was not affected by the defocusing, and it made good use of many kinds of characteristics of the images. So this new mehtod can get very precise segmentation; it is effective for defocusing urinary sediment image segmentation.
Algorithms ; Humans ; Image Interpretation, Computer-Assisted ; Urinalysis ; methods ; Urine

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

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