Imaging technology

About: Imaging technology is a research topic. Over the lifetime, 1450 publications have been published within this topic receiving 26186 citations.

Low Dimensional Methods for High Dimensional Magnetic Resonance Imaging

Abstract: Author(s): Ong, Frank | Advisor(s): Lustig, Michael | Abstract: Magnetic Resonance Imaging (MRI) is an amazing imaging modality in many aspects. It offers one of the best imaging contrast for visualizing soft issues. It has no ionizing radiation at all. Its flexibility has also enabled many applications, including assessing blood flow, imaging brain activity via oxygenation contrast, and measuring tissue stiffness. Since MRI was invented, this imaging technology has saved numerous lives, and has been the frontier of biomedical and engineering research.On the other hand, imaging speed remains a main limitation of MRI. Inherently, MRI takes time to collect measurements, and often requires minutes to complete a scan. In this regard, MRI is quite similar to early cameras: Subjects have to be motionless for minutes to obtain an image, which is uncomfortable to patients. This often leads to motion and motion artifacts. When severe motion artifacts occur, scans have to be repeated.This dissertation aims to change that by developing techniques to reconstruct three-dimensional (3D) dynamic MRI from continuous acquisitions. An ideal 3D dynamic scan would be able to resolve all dynamics at a high spatiotemporal resolution. Subjects would not have to be motionless. The comprehensive information in the single scan would also greatly simplify clinical workflow. While this dissertation has not achieved this ideal scan yet, it proposes several innovations toward this goal. In particular, www.doi.org/10.6084/m9.figshare.7464485 shows a 3D rendering of a reconstruction result from this dissertation. Arbitrary slices at different orientation can be selected over time. Respiratory motion, contrast enhancements, and even slight bulk motion can be seen.The main challenge in high resolution 3D dynamic MRI is that the reconstruction problem is inherently underdetermined and demanding of computation and memory. To overcome these challenges, this dissertation builds on top of many fundamental methods, including non-Cartesian imaging, parallel imaging and compressed sensing. In particular, this dissertation heavily relies on the compressed sensing framework, which has three components: 1) the image of interest has a compressed signal representation. 2) MRI can acquire (pseudo)-randomized samples in k-space, which provides incoherent encoding of the underlying image. 3) sparsity/compressibility can be efficiently enforced in reconstruction to recover the compressed representation from the undersampled measurements.In this dissertation, I propose a multiscale low rank model that can compactly represent dynamic image sequences. The resulting representation can be applied beyond MRI, and is useful for other applications, such as motion separation in surveillance video. With the multiscale low rank representation, I propose a technique incorporating stochastic optimization to efficiently reconstruct 3D dynamic MRI. This makes it feasible to run such large-scale reconstructions on local workstations. To further speed up the reconstruction time, I propose accelerating the convergence of non-Cartesian reconstruction using a specially designed preconditioner. Finally, I leverage external undersampled datasets to further improve reconstruction quality using convolutional sparse coding.

Development of Small Living Animal Imaging Technology

Abstract: With the development of small animal imaging technology,non-invasive imaging in small living animal models has gained increasing importance in pre-clinical research.Five kinds of small animal imaging technology, including optical imaging,PET/SPECT,MRI,CT and ultrasound imaging,were reviewed from the aspects of their characteristics and main applications.Meanwhile,the advantages and limitations of them were summarized.The trends of small living animal imaging technology were discussed as well.

Research on Color Reproduction of Mural Based on Multi-Spectral Imaging Technology

Abstract: The spectral reflectance reconstruction by camera's signal response is an important research content in the field of color science engineering. In this paper the multispectral imaging technology was studied to reconstruct the spectral reflectance of Chinese mural patches based on Matrix R method. The experimental results shows that the reconstructed precision of Matrix R method is good. Then we reproduced the color of mural by using Matrix R method to reconstruct the spectral reflectance which had a better color reproduction effect. INTRODUCTION The application of color image can be applied everywhere in people's daily life. With society progressing and science technology developing, the requirement of color image is also improved, which inevitably promotes color reproduction technology to develop. There are several methods for traditional color reproduction such as reproduction based on chroma, correct color reproduction, equivalent color reproduction and color reproduction of the corresponding colors, etc. Because of the metamerism phenomenon, although these methods can successfully achieve the color reproduction without achieving color unconditional reproduction. Spectral reflectance as the inherent physical properties of object, does not change with the light source and the observer. So using the spectral reflectance to achieve color reproduction has high stability and reliability. color reproduction based on Spectral reflectance has gradually becoming an important technical method for current cross-media color reproduction, which can effectively eliminate the problem of metamerism phenomenon and achieving unconditional color matching [1] . Using multi-spectral color reproduction technology to obtain true color reduction could record the color more detailed characteristics. Sampling the spectral reflectance to multi-band can effectively achieve a high quality color reproduction which solve the issue that data precision is too low in traditional mode[2-3]. Therefore, using multi-spectral imaging technology to obtain multi-spectral images of objects to achieve the true color reproduction meets the cultural relics reproduction of high-precision needs. In this paper, we used the multispectral imaging system to collect the channel response values of the training samples and the test samples. Then we used the spectral reflectance reconstruction algorithm _________________________________________ Zhan Wang, Shaanxi Provincial Institute of Cultural Relics Protection, Xi'an, China Ke Wang, Yanqun Long, Weichao Wang, Lijuan Zhao, School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an, China wk1307@126.com.

Blind-deconvolution Airy-beam photoacoustic microscopy for removing the sidelobe

Abstract: As an emerging nondestructive imaging technology, photoacoustic imaging (PAI), which is based on photoacoustic effect, combines the advantages of the high resolution and contrast of optical imaging and the high penetration depth of acoustic imaging. Thereinto, as a branch of photoacoustic imaging, photoacoustic microscopy inherited the advantages of photoacoustic imaging. The unique focusing mode of photoacoustic microscopy can meet the requirements of higher resolution in biological imaging and it has gained extensive applications in medical science field. In our previous work, in order to solve the shortcoming of traditional photoacoustic microscopy with a small depth of field, we have built a simulation platform for Airy-beam photoacoustic microscopy based on K-Wave MATLAB toolbox, which uses Airybeam to excite the initial photoacoustic signal. As non-diffraction beam, Airy-beam features the capacity of large depth of field. However, Airy-beam has sidelobe, which makes the edges of the image blurred. Convolution is a mathematical method of integrating transformations. The imaging result of optical system is the result of convolution of the sample and PSF of the system. PSF convolves with the sample, resulting in blurred image and reduced image resolution. The image can be restored by appropriate deconvolution techniques. In this paper, in order to weaken the influence of Airybeam’s sidelobe on the imaging results, Lucy-Richardson (LR) Algorithm is used to deconvolve the imaging results to obtain clearer restored images. LR Algorithm is a nonlinear iterative restoration algorithm based on Bayesian conditional probability model, and it is assumed that pixels in fuzzy images meet Possion distribution, and its optimal estimation criterion is maximum likelihood criterion. Using LR Algorithm for Airy-beam photoacoustic microscopy can greatly improve the system resolution and clearer imaging results can be obtained.

A Systematic Approach to 4D Radiation Therapy – Integration of 4D Medical Imaging into 4D Radiation Therapy

Abstract: Historically, the evolution of radiation oncology has been closely linked to the advances in medical imaging. Recent breakthroughs in imaging technology, particularly 4D medical imaging, have injected new momentum into radiation oncology, shedding new light on revitalizing this century old treatment modality. This eventually led to the creation of a primitive form of 4D radiation therapy (4DRT). 4DRT can be defined as a combination of using 4D imaging to guide radiation treatment planning, correcting for daily set-up errors through either patient repositioning or plan adaptation, and controlling radiation delivery based on internal or external fiducials that can be continuously tracked. 4DRT introduces the time dimension into the 3DRT in order to compensate for patient motion/changes occurring either during a single fraction (intra-fractional) or between successive fractions (inter-fractional). The major advantages of 4DRT are high-precision dose conformity, minimized normal tissue complication probability, and possible further dose escalation to the target. To maximize the potential benefits of 4D medical imaging and promising improvements in patient survival and quality of life, an integrative and systemic approach to 4DRT is essential. Without such an integrated multi-disciplinary strategy, 4DRT would only remain as an ideal concept. Here, we propose a comprehensive approach that integrates 4D medical imaging into each of the key steps in 4DRT, including 4D simulation, 4D treatment planning, and 4D treatment delivery. 4D Simulation The 4D imaging modalities, including 4DCT, 4DMRI, 4DPET, and 4DSPECT, should be used to provide needed clinical information. To provide a time-stamped indication of the motion stage (amplitude or phase), external or internal fiducial markers should be used for monitoring patient motion in 4DCT imaging. With this tracking information, image acquisition can be prospectively gated and the acquired images can be retrospectively sorted into image bins reflecting the different respiratory phases. One of the three respiratory tracking techniques should be considered: (1) optical tracking methods using an infrared laser with reflectors placed on thorax or abdomen, (2) use of a spirometer to measure tidal ventilation volume, (3) use of Bellows pressure sensor below diaphragm for monitoring anatomical volume change. 4D Treatment Planning An internal target volume (ITV) with more precise margin covering the moving clinical target volume (CTV) should be delineated on either 4DCT or 4DMRI. In addition, PET or SPECT 3D images should also be employed to accurately determine the true extent of the CTV. A full 4DCT image (multiple 3DCT images) acquired at each of the respiratory phases (at least eight) should be used to create an independent treatment plan for each phase. The physician contoured target and organs at risk (OAR) should be preserved through deformable image registration. Plans should be computed using adaptive dose calculation technique. 4D Treatment Delivery On-site Imaging for Patient Setup: The 2D/3D/4D imaging of the patient in the treatment position should be used to improve setup accuracy. These include multiple 2D x-ray imaging, optical 3D superficial imaging, kV cone-beam CT (CBCT) imaging, helical MVCT imaging, and 4DCT imaging. Real-time Target Tracking: Superficial motion tracking and external surrogates are useful in determining the extent of respiratory motion, but are not sufficient for tracking tumor motion and change in volume and shape. Therefore, internal fiducial markers should be implanted into or around the target to minimize ionization radiation to the patient. Real-time Dose Delivery: Real-time treatment delivery should be guided by a target tracking feedback system. Currently, this has not been feasible in most of the clinics. The key is the combination of the individual 4DRT components to form a clinically feasible approach.