A CT 3-D image is reconstructed based on a lot of 2-D slice images. A new 3-D image reconstruction method, presented in this paper, is to use the helical scan continuity, sufficient condition of image reconstruction and the raw data from a few helical scan cycles to reconstruct,by a direct interpolation algorithm, 2-D images and then 3-D images.
Algorithms ; Humans ; Image Processing, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Reproducibility of Results ; Tomography, Spiral Computed ; methods

Topological description and matching are committed steps for three-dimensional reconstruction of vessel tree from two angiograms. Binary tree is proposed to describe the two-dimensional vessel tree. "Node Weight" and "Similar Node" are defined in order to get better description. Vessel segments in two images are matched by the preorder traversal of the binary trees, and the method is proved fast and accurate.
Algorithms ; Angiography ; methods ; Computer Simulation ; Humans ; Image Processing, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; methods ; Models, Biological ; Pattern Recognition, Automated ; methods ; Radiographic Image Enhancement ; methods

Multiscale pyramid image enhancement algorithm is an usual way to enhance the Digital Radiography (DR) images. However, the process of enhancement takes much of time because of the fine resolution of DR images. A new method of accelerating DR image enhancement based on Compute Unified Device Architecture (CUDA) is presented in this paper. This method completes a large amount of convolution operations in spatial domain involved in the multiscale pyramid image enhancement algorithm by using the Graphic Processing Unit (GPU). The experimental results show that the proposed method is very efficient for accelerating DR image enhancement.
Algorithms ; Humans ; Radiographic Image Enhancement ; methods ; Signal Processing, Computer-Assisted

The data-sampling speed of cone-beam CT is faster than that of fan-beam CT, so the cardiac image will be more and more perfect in cone-beam CT with the improvement of the reconstruction algorithm. A new scanning framework of double cone-beam, which has improved FDK algorithm is presented, and a method of 3-D cardiac image reconstruction based on the new scanning framework is designed resulting in a better cardiac image quality.
Algorithms ; Heart ; diagnostic imaging ; Humans ; Image Processing, Computer-Assisted ; methods ; Imaging, Three-Dimensional ; methods ; Models, Statistical ; Radiographic Image Enhancement ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Tomography, X-Ray Computed ; methods

PURPOSE: This study evaluated the diagnostic accuracy of the reverse contrast mode in intraoral digital radiography for the detection of proximal dentinal caries, in comparison with the original digital radiographs. MATERIALS AND METHODS: Eighty extracted premolars with no clinically apparent caries were selected, and digital radiographs of them were taken separately in standard conditions. Four observers examined the original radiographs and the same radiographs in the reverse contrast mode with the goal of identifying proximal dentinal caries. Microscopic sections 5 microm in thickness were prepared from the teeth in the mesiodistal direction. Four slides prepared from each sample used as the diagnostic gold standard. The data were analyzed using SPSS (alpha=0.05). RESULTS: Our results showed that the original radiographs in order to identify proximal dentinal caries had the following values for sensitivity, specificity, positive predictive value, negative predictive value, and accuracy, respectively: 72.5%, 90%, 87.2%, 76.5%, and 80.9%. For the reverse contrast mode, however, the corresponding values were 63.1%, 89.4%, 87.1%, 73.5%, and 78.8%, respectively. The sensitivity of original digital radiograph for detecting proximal dentinal caries was significantly higher than that of reverse contrast mode (p<0.05). However, no statistically significant differences were found regarding specificity, positive predictive value, negative predictive value, or accuracy (p>0.05). CONCLUSION: The sensitivity of the original digital radiograph for detecting proximal dentinal caries was significantly higher than that of the reversed contrast images. However, no statistically significant differences were found between these techniques regarding specificity, positive predictive value, negative predictive value, or accuracy.
Bicuspid ; Dental Caries ; Dentin* ; Image Enhancement ; Image Processing, Computer-Assisted ; Radiographic Image Enhancement* ; Radiography, Dental, Digital ; Sensitivity and Specificity ; Tooth

OBJECTIVETo explore the effects of image post-processing parameters on DR chest radiograph for the diagnosis of pneumoconiosis.

METHODSEighty three coal miners were examined with high-kV and DR chest radiographs at the same time. Image post-processing parameters (density, contrast and so on) were designed in a Philips Essenta DR machine were designed, then differences of image quality between high-kV and DR chest radiographs were compared.

RESULTSAfter regulating image and proceeding the parameters, the OD (optical density) values of high density areas in the upper-middle lung fields, subphrenic and direct exposure areas were 1.58 +/- 0.10, 0.23 +/- 0.02 and 2.80 +/- 0.21, respectively. The quality of chest films met the requirements of diagnostic criteria of pneumoconiosis. The rate of excellent chest films for DR chest radiograph was 95.18%, which was significantly higher than that (80.72%) for high-kV chest radiograph (P < 0.01).

CONCLUSIONAppropriate parameters of image post-processing can make DR chest radiograph to meet the requirements of chest radiograph quality for the diagnosis of pneumoconiosis.

OBJECTIVETo establish the optimal image post-processing parameters for digital chest radiography as preliminary research for introducing digital radiography (DR) to pneumoconiosis diagnosis in China.

METHODSA total of 204 pneumoconiosis patients and 31 dust-exposed workers were enrolled as the subjects in this research. Film-screen radiography (FSR) and DR images were taken for all subjects. DR films were printed after raw images were processed and parameters were altered using DR workstation (GE Healthcare, U.S.A.). Image gradations, lung textures, and the imaging of thoracic vertebra were evaluated by pneumoconiosis experts, and the optimal post-processing parameters were selected. Optical density was measured for both DR films and FSR films.

RESULTSFor the DR machine used in this research, the contrast adjustment (CA) and brightness adjustment (BA) were the main parameters that determine the brightness and gray levels of images. The optimal ranges for CA and BA were 115%∼120% and 160%∼165%, respectively. The quality of DR chest films would be optimized when tissue contrast was adjusted to a maximum of 0.15, edge to a minimum of 1, and both noise reduction and tissue equalization to0.The failure rate of chest DR (0.4%) was significantly lower than that of chest FSR (17%) (P < 0.05).

CONCLUSIONAfter appropriate image post-processing on DR machine purchased from GE Healthcare, the DR chest films can meet all requirements for the quality of chest X-ray films in the Chinese diagnostic criteria for pneumoconiosis.

A wavelet threshold denoising algorithm for CR images is put forward here . A noised CR image is decomposed into wavelet coefficients, which are processed by the algorithm, and the denoised CR image is reconstructed based on the processed coefficients. Examples are too presented to demonstrate the efficiency of the algorithm on denoising and, maintaining the detail of the CR images.
Algorithms ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods ; Radiography ; methods ; Signal Processing, Computer-Assisted

Extracting landmark geometric data in C-arm X-ray images is a key technique of camera calibration process in a fluoroscopic-image-based surgical navigation system. The geometric data is the basis of X-ray image distortion correction and C-arm camera calibration. In this paper we present an integrated clustering algorithm for landmark geometric data extraction. This proposed alorithm, with the advantages of an adaptive thresholding method as well as of a fast quasi connected-component labeling method, needs only one pass to extract the needed geometric data in a gray scale image. It is of high executive efficiency and good robustness as well.
Algorithms ; Calibration ; Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; Surgery, Computer-Assisted ; methods

In order to solve the time-consuming problem in volume CT image reconstruction field, we brought forward a fast reconstructive algorithm method to fit the clinic medicine. First, using the great parallel and Floating-Point power of graphic processing unit (GPU), we proposed a volume CT GPU- based reconstruction method. Second, in order to reduce the repetitive operation, we separated the geometry computation and pixel computation. As a result, the computation efficiency was further improved. At last, based on the background of medical engineering, the parallel of volume CT scan and reconstruction was implemented. The results demonstrated that the volume CT reconstruction time could reduce up to 70 times compared to the previous one in common PC by the fast reconstructive algorithm method.
Algorithms ; Computer Graphics ; Cone-Beam Computed Tomography ; instrumentation ; methods ; Humans ; Image Processing, Computer-Assisted ; methods ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods