A fast microscopic image mosaicing method is proposed in this paper by making a study of the mosaic methods and the characteristics of microscopic images. In the paper, invariant local features based on normalized moment of inertia (NMI) are used to select the matching points and calculate the spatial translation. The experimental results demonstrate that this algorithm can achieve fast, effective microscopic image mosaicing.
Algorithms ; Image Enhancement ; methods ; Photomicrography ; methods

The scale of local structure is a key parameter in medical image registration. Unfortunately, no much attention has been paid to the scale selection for the local structures in the images. This paper proposes a data-driven scale selection method for local structures in the image. By using minimal description length criterion to maximize the posterior probability of local structure region with coherence constraint based on the Markov random field model, an optimal scale for each local structure, which is segmented with super-pixel representation, is assigned in terms of variance in a discrete anisotropic scale space. Therefore, the local structure's scale can be selected for further non-rigid medical image registration.
Algorithms ; Image Enhancement ; methods ; Image Processing, Computer-Assisted ; methods

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

No abstract available.
*Radiographic Image Enhancement ; Mammography/*methods ; Humans

Based on analyzing image edge cloning theory and algorithms, a marginal clone algorithm is proposed with a combination of edge connectivity and noise removal algorithm. Simulation results show that the edge image detected by the algorithm has solved problems of traditional edge discontinuities and tsereve noise. Moreover, it has better edge recognition performance.
Algorithms ; Humans ; Image Enhancement ; methods ; Retinal Vessels

A small HIFU system was used to investigate the phase-shift droplet vaporization in vivo and its effect on thermal absorption in tissue-mimicking phantoms. The experiments demonstrated that droplets could be vaporized to bubbles in vivo by the small HIFU system and the volume of bubbles could increase by tens of times. With appropriate droplets concentration, lesion volume produced by HIFU could be increased significantly under the same HIFU parameter.
Fluorocarbons ; Image Enhancement ; Ultrasonic Therapy ; methods

A novel DR image denoising algorithm based on Laplace-Impact mixture model in dual-tree complex wavelet domain is proposed in this paper. It uses local variance to build probability density function of Laplace-Impact model fitted to the distribution of high-frequency subband coefficients well. Within Laplace-Impact framework, this paper describes a novel method for image denoising based on designing minimum mean squared error (MMSE) estimators, which relies on strong correlation between amplitudes of nearby coefficients. The experimental results show that the algorithm proposed in this paper outperforms several state-of-art denoising methods such as Bayes least squared Gaussian scale mixture and Laplace prior.
Algorithms ; Models, Statistical ; Radiographic Image Enhancement ; methods

On account of different thickness of tissues absorbing different doses of X ray, it is difficult to display anatomical details of different tissues on a single screen of DR equipment. In order to resolve this problem, the self-adaptive reverse S mode transformation algorithm is presented in the paper, which can modify darker regions and brighter regions respectively, and improve the visibility of weakly details.
Algorithms ; Radiographic Image Enhancement ; instrumentation ; methods

OBJECTIVE: To improve the performance quality of mammography X-ray system, and to decrease misdiagnoses. METHODS: Quality assurance was tested and controlled from such aspect as measurement of half value layer, beam quality assessment, breast entrance exposure average glandular dose, tube tunsion accuracy and reproducibility, and radiation output. RESULTS: The image contrast, mistiness and noise were optimized. CONCLUSION With the quality assurance of the digital mammography X-ray system, the variations of the performance parameters remain in the range of permission, thus improving the quality of mammography.
Humans ; Image Enhancement ; instrumentation ; Mammography ; instrumentation ; methods ; Quality Control ; Radiographic Image Enhancement ; instrumentation

The application of KV, MV real-time digital images and 3D reconstructed radiography in quality assurance of radiotherapy, provides effective means to verify the beam center and therapeutic range, calibrate the positioning accuracy and inspect the characteristics of radiotherapy equipment and radiation physics, greatly improves the quality and accuracy of radiotherapy.
Quality Assurance, Health Care ; methods ; Radiographic Image Enhancement ; Radiotherapy ; methods