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

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

Look-up table (LUT) algorithms have been widely used in digital signal processing, but the article on the application of LUT algorithms in digital subtraction angiography was rarely reported. In this article, the effect of different LUT algorithms on digital subtraction angiography images is introduced. The result reveals that different LUT algorithms can bring about different effects of image. Based on analysis and comparison, we deem it possible to acquire improved images of DSA by use of some LUT algorithms with image processing.
Algorithms ; Angiography, Digital Subtraction ; methods ; Humans ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; methods

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

Because of the difference in organic density, a simple and effective method for exponent restraint of active edge is applied to X-ray image of bone. And it is easy to use histogram method to get the active image of bone. At last, by associating it with Canny method, the edge of bone can be abstracted from a complex X-ray image.
Algorithms ; Bone and Bones ; diagnostic imaging ; Humans ; Radiographic Image Enhancement ; methods ; Radiographic Image Interpretation, Computer-Assisted ; 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

OBJECTIVETo conduct a systematic review of studies reporting the comparison of digital radiography (DR) with conventional film-screen radiograph (FSR) in the screening and recognition of pneumoconiosis worldwide, to evaluate the feasibility of DR in the screening and recognition of pneumoconiosis, to analyze the similarity and difference between DR and FSR, to explore the main challenge to utilize DR in the future.

METHODSThe national and international databases were systematically searched for original articles on DR for screening and recognition of pneumoconiosis published from first Jan 1998 to first Nov 2013, making evaluation and selection of them, and qualitative data and quantitative data were extracted independently from the selected articles and systematically reviewed.

RESULTSFive hundred and twenty articles were found and evaluated and nine of them met the inclusion criteria of systematic review. The research time started from 2002 to 2011 whose objects mainly came from pneumoconiosis cases and dust-exposed workers and control population examined with DR and FSR using the high kV radiography from 120 to 130 kV. The chest radiographs were read at blind and random and standard control method. There were only two papers compare the validity of DR and FSR for recognition and classification of pneumoconiosis using gold standards. There were still some diversity of imaging processing and imaging reading without design and assessment using Standards for Reporting of Diagnostic Accuracy (STARD) in these researches. The evaluation index of the nine articles include detection rate of small opacities, crude agreement, Kappa value of Kappa Consistency Test, Area Under the Curve of ROC, etc. Seven of the nine selected articles estimated DR has generally produced superior image qualities compared to FSR. Four papers had a conclusion that DR could be equivalent to FSR in identification of shapes and profusion of small opacities and in classification of pneumoconiosis. Five papers considered DR had higher presence of pneumoconiosis comparing with FSR especially in recognition the pneumoconiosis of category 1. The variation between different film formats of DR and FSR were smaller than that within and between readers for classification of pneumoconiosis.

CONCLUSIONAlthough there are still some imperfections in the existent researches to solve, DR can be equivalent to FSR in screening and recognition of pneumoconiosis. It is necessary to develop technical specifications of DR and standard digital chest radiographs for pneumoconiosis including both hard copy and soft copy, and develop an evaluation criterion on chest images of DR.

We presented a new method for vessel segmentation and vascular structure recognition for coronary angiographic images. During vessel segmentation, a new vessel function was proposed to attain vessel feature map. Then the region growing algorithm was implemented with an automatic selection of seed point, extraction of main vessel branch, and vessel detail repairing. In the algorithm of vascular structure recognition, a fuzzy operator was used, which can detect the structures of vascular segments, bifurcations, crosses, and tips. The experimental results indicated that there was about 5 percent larger vessel region which was extracted by the proposed segmentation method than that by the simple region growing algorithm, and several thinner vessels were resumed from the lower gray region. The results also indicated that the fuzzy operator could correctly infer the simulative and real vessel structure with 100% and 90.59% correctness rate on the average, respectively.
Algorithms ; Coronary Angiography ; Humans ; Radiographic Image Enhancement ; methods ; X-Rays

Humans ; Pneumoconiosis ; diagnostic imaging ; Radiographic Image Enhancement ; Radiography ; methods