Adaptive Visual Saliency Feature Enhancement of CBCT for Image-Guided Radiotherapy

Unlike the high imaging radiation dose of computed tomography (CT), cone-beam CT (CBCT) has smaller radiation dose and presents less harm to patients. Therefore, CBCT is often used for target delineation, dose planning, and postoperative evaluation in the image-guided radiotherapy (IGRT) of various cancers. In the process of IGRT, CBCT images usually need to be collected multiple times in a radiotherapy stage for postoperative evaluation. The effectiveness of radiotherapy is measured by comparing and analyzing the registered CBCT and the source CT image obtained before radiotherapy. Hence, the registration of CBCT and CT is the most important step in IGRT. CBCT images usually have poor visual effects due to the small imaging dose used, which adversely affects the registration performance. In this paper, we propose a novel adaptive visual saliency feature enhancement method for CBCT in IGRT. Firstly, we denoised CBCT images using a structural similarity based low-rank approximation model (SSLRA) and then enhanced the denoised results with a visual saliency feature enhancement (VSFE)-based method. Experimental results show that the enhancement performance of the proposed method is superior to the comparison enhancement algorithms in visual objective comparison. In addition, the extended experiments prove that the proposed enhancement method can improve the registration accuracy of CBCT and CT images, demonstrating their application prospects in IGRT-based cancer treatment

Multi-Intensity Optimization-Based CT and Cone Beam CT Image Registration

Cancer is a highly lethal disease that is mainly treated by image-guided radiotherapy. Because the low dose of cone beam CT is less harmful to patients, cone beam CT images are often used for target delineation in image-guided radiotherapy of various cancers, especially in breast and lung cancer. However, breathing and heartbeat can cause position errors in images taken during different periods, and the low dose of cone beam CT also results in insufficient imaging clarity, rendering existing registration methods unable to meet the CT and cone beam CT registration tasks. In this paper, we propose a novel multi-intensity optimization-based CT and cone beam CT registration method. First, we use a multi-weighted mean curvature filtering algorithm to preserve the multi-intensity details of the input image pairs. Then, the strong edge retention results are registered using and intensity-based method to obtain the multi-intensity registration results. Next, a novel evaluation method called intersection mutual information is proposed to evaluate the registration accuracy of the different multi-intensity registration results. Finally, we determine the optimal registration transformation by intersection mutual information and apply it to the input image pairs to obtain the final registration results. The experimental results demonstrate the excellent performance of the proposed method, meeting the requirements of image-guided radiotherapy

Multi-Intensity Optimization-Based CT and Cone Beam CT Image Registration

Cancer is a highly lethal disease that is mainly treated by image-guided radiotherapy. Because the low dose of cone beam CT is less harmful to patients, cone beam CT images are often used for target delineation in image-guided radiotherapy of various cancers, especially in breast and lung cancer. However, breathing and heartbeat can cause position errors in images taken during different periods, and the low dose of cone beam CT also results in insufficient imaging clarity, rendering existing registration methods unable to meet the CT and cone beam CT registration tasks. In this paper, we propose a novel multi-intensity optimization-based CT and cone beam CT registration method. First, we use a multi-weighted mean curvature filtering algorithm to preserve the multi-intensity details of the input image pairs. Then, the strong edge retention results are registered using and intensity-based method to obtain the multi-intensity registration results. Next, a novel evaluation method called intersection mutual information is proposed to evaluate the registration accuracy of the different multi-intensity registration results. Finally, we determine the optimal registration transformation by intersection mutual information and apply it to the input image pairs to obtain the final registration results. The experimental results demonstrate the excellent performance of the proposed method, meeting the requirements of image-guided radiotherapy

Infrared and Visible Image Fusion Combining Interesting Region Detection and Nonsubsampled Contourlet Transform

The most fundamental purpose of infrared (IR) and visible (VI) image fusion is to integrate the useful information and produce a new image which has higher reliability and understandability for human or computer vision. In order to better preserve the interesting region and its corresponding detail information, a novel multiscale fusion scheme based on interesting region detection is proposed in this paper. Firstly, the MeanShift is used to detect the interesting region with the salient objects and the background region of IR and VI. Then the interesting regions are processed by the guided filter. Next, the nonsubsampled contourlet transform (NSCT) is used for background region decomposition of IR and VI to get a low-frequency and a series of high-frequency layers. An improved weighted average method based on per-pixel weighted average is used to fuse the low-frequency layer. The pulse-coupled neural network (PCNN) is used to fuse each high-frequency layer. Finally, the fused image is obtained by fusing the fused interesting region and the fused background region. Experimental results demonstrate that the proposed algorithm can integrate more background details as well as highlight the interesting region with the salient objects, which is superior to the conventional methods in objective quality evaluations and visual inspection

A Fast Image Guide Registration Supported by Single Direction Projected CBCT

Image registration is an important research topic in medical image-guided therapy, which is dedicated to registering the high-dose imaging sequences with low-dose/faster means. Registering computer tomography (CT) scanning sequences with cone beam computer tomography (CBCT) scanning sequences is a typical application and has been widely used in CBCT-guided radiotherapy. The main problem is the difference in image clarity of these two image sequences. To solve this problem, for the single projection image sequence matching tasks encountered in medical practice, a novel local quality based curved section encoding strategy is proposed in this paper, which is called the high-quality curved section (HQCS). As an optimized cross-section regularly encoded along the sequence of image, this curved section could be used in order to solve the matching problem. Referencing the independent ground truth provided by medical image physicians, with an experiment combined with the four most widely used indicators used on image registration, matching performance of HQCS on CT/CBCT datasets was tested with varying clarity. Experimental results show that the proposed HQCS can register the CT/CBCT effectively and outperforms the commonly used methods. Specifically, the proposed HQCS has low time complexity and higher scalability, which indicates that the application enhanced the task of diagnosis

Research and Application of Polycarboxylic Acid Water Reducer with Different Molecular Weight

In this paper, a polycarboxylic water reducing agent was synthesized by using Methylallyl polyethylene glycol (HPEG) with molecular weight of 1200, 2400, 2800 and 3400 under the same conditions, C80 concrete tests were performed on these four molecular weight superplasticizers, verify the effect of different molecular weight polycarboxylic acid water reducer in C80 pumping concrete, finally, a kind of low molecular weight polycarboxylic acid water reducer with viscosity reducing effect in high-grade concrete is obtained, which can promote pumping of high-grade concrete

A Fast Image Guide Registration Supported by Single Direction Projected CBCT

Image registration is an important research topic in medical image-guided therapy, which is dedicated to registering the high-dose imaging sequences with low-dose/faster means. Registering computer tomography (CT) scanning sequences with cone beam computer tomography (CBCT) scanning sequences is a typical application and has been widely used in CBCT-guided radiotherapy. The main problem is the difference in image clarity of these two image sequences. To solve this problem, for the single projection image sequence matching tasks encountered in medical practice, a novel local quality based curved section encoding strategy is proposed in this paper, which is called the high-quality curved section (HQCS). As an optimized cross-section regularly encoded along the sequence of image, this curved section could be used in order to solve the matching problem. Referencing the independent ground truth provided by medical image physicians, with an experiment combined with the four most widely used indicators used on image registration, matching performance of HQCS on CT/CBCT datasets was tested with varying clarity. Experimental results show that the proposed HQCS can register the CT/CBCT effectively and outperforms the commonly used methods. Specifically, the proposed HQCS has low time complexity and higher scalability, which indicates that the application enhanced the task of diagnosis

Parameter Analysis of Wall Thickness of Cured-in-Place Pipe Linings for Semistructured Rehabilitation of Concrete Drainage Pipe

Frequent accidents caused by underground pipeline damage are a widespread societal concern. Trenchless rehabilitation methods, particularly cured-in-place pipe (CIPP) lining, are increasingly used for pipeline repair with great success. Existing research is mainly concerned with practical improvements in rehabilitation and evaluating the performance of rehabilitation. In this study, the model of corroded buried concrete pipeline that had been rehabilitated with CIPP was established using numerical methods, and the Mesh-based parallel-Code Coupling Interface (MpCCI) was used to investigate multifield coupling effects of soil pressure, traffic load, and fluid-structure interactions. Moreover, the influences of corrosion depth, corrosion width, traffic load, cover depth, and water quantity on CIPP wall thickness were compared and analyzed. The result shows that maximum principal stress and vertical displacement of pipeline markedly decreased after CIPP rehabilitation, and thus the new CIPP can carry loads in a deteriorated pipe. Stress and displacement of the composite pipe liner were positively correlated with corrosion depth and negatively correlated with corrosion width. Increase in traffic load rapidly increases von Mises stress of CIPP, and increase in cover depth rapidly increases maximum principal stress of pipeline. Water flow has little effect on the pipe liner, and flow capacity increases slightly after CIPP rehabilitation. CIPP wall thickness was positively correlated with corrosion depth, traffic load, cover depth, and water quantity and negatively correlated with corrosion width

Research and Application of Polycarboxylic Acid Water Reducer with Different Molecular Weight

In this paper, a polycarboxylic water reducing agent was synthesized by using Methylallyl polyethylene glycol (HPEG) with molecular weight of 1200, 2400, 2800 and 3400 under the same conditions, C80 concrete tests were performed on these four molecular weight superplasticizers, verify the effect of different molecular weight polycarboxylic acid water reducer in C80 pumping concrete, finally, a kind of low molecular weight polycarboxylic acid water reducer with viscosity reducing effect in high-grade concrete is obtained, which can promote pumping of high-grade concrete

Multifocus Color Image Fusion Based on NSST and PCNN

This paper proposed an effective multifocus color image fusion algorithm based on nonsubsampled shearlet transform (NSST) and pulse coupled neural networks (PCNN); the algorithm can be used in different color spaces. In this paper, we take HSV color space as an example, H component is clustered by adaptive simplified PCNN (S-PCNN), and then the H component is fused according to oscillation frequency graph (OFG) of S-PCNN; at the same time, S and V components are decomposed by NSST, and different fusion rules are utilized to fuse the obtained results. Finally, inverse HSV transform is performed to get the RGB color image. The experimental results indicate that the proposed color image fusion algorithm is more efficient than other common color image fusion algorithms