Imaging technology

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

Progress of photoacoustic imaging combined with targeted photoacoustic contrast agents in tumor molecular imaging

Abstract: Molecular imaging visualizes, characterizes, and measures biological processes at the molecular and cellular level. In oncology, molecular imaging is an important technology to guide integrated and precise diagnosis and treatment. Photoacoustic imaging is mainly divided into three categories: photoacoustic microscopy, photoacoustic tomography and photoacoustic endoscopy. Different from traditional imaging technology, which uses the physical properties of tissues to detect and identify diseases, photoacoustic imaging uses the photoacoustic effect to obtain the internal information of tissues. During imaging, lasers excite either endogenous or exogenous photoacoustic contrast agents, which then send out ultrasonic waves. Currently, photoacoustic imaging in conjunction with targeted photoacoustic contrast agents is frequently employed in the research of tumor molecular imaging. In this study, we will examine the latest advancements in photoacoustic imaging technology and targeted photoacoustic contrast agents, as well as the developments in tumor molecular imaging research.

Benefits of lung modeling by high-quality three-dimensional computed tomography for thoracoscopic surgery

Abstract: Although video-assisted thoracoscopic surgery (VATS) has become widely used as a less invasive therapeutic procedure for lung cancer, precise anatomical knowledge of each case remains crucial and greatly contributes to the safety of thoracoscopic surgery. Thus, the development of three-dimensional (3D) imaging technology is anticipated to provide surgeons with essential visualized information of anatomical structures. In this review, we evaluate the pragmatic features of 3D imaging technology for thoracoscopic lung cancer surgery, focusing on complicated surgeries and preoperative evaluation of pulmonary functions or tumor features. We also discuss 3D imaging software and the applications of the 3D image analysis system. Finally, we present our perspectives on the 3D imaging technology for thoracoscopic surgery.

Sparse Reconstruction for Radar Imaging based on Quantum Algorithms

Abstract: The sparse-driven radar imaging can obtain the high-resolution images about target scene with the down-sampled data. However, the huge computational complexity of the classical sparse recovery method for the particular situation seriously affects the practicality of the sparse imaging technology. In this paper, this is the first time the quantum algorithms are applied to the image recovery for the radar sparse imaging. Firstly, the radar sparse imaging problem is analyzed and the calculation problem to be solved by quantum algorithms is determined. Then, the corresponding quantum circuit and its parameters are designed to ensure extremely low computational complexity, and the quantum-enhanced reconstruction algorithm for sparse imaging is proposed. Finally, the computational complexity of the proposed method is analyzed, and the simulation experiments with the raw radar data are illustrated to verify the validity of the proposed method.

Rapid high-resolution ultrasonic imaging detection method

Abstract: The invention discloses a rapid high-resolution ultrasonic imaging detection method. According to the method, by a super sub-sampling data imaging technology and a super-resolution technology, the problem of how to obtain relatively few sampling data and high-resolution ultrasonic imaging is solved under the condition of not increasing the cost of hardware equipment; and meanwhile, the imaging speed and quality are improved. According to the rapid high-resolution ultrasonic imaging detection method, the super sub-sampling imaging technology and the super-resolution technology are organically fused together and are applied to an ultrasonic detection system from compressed sensing and parse expansion theories as the starting point, so that the imaging speed and the imaging resolution are greatly improved on the present basis.

Compression and reconstruction of medical image sequences

Abstract: Many important imaging applications generate a sequence of images that are (or can be made to be) a spatially invariant image sequence with linearly additive contributions from the components that form the images. They include functional images in nuclear medicine, multiparameter MR imaging, multi-energy x-ray imaging for DR and CT, and multispectral satellite images. Recent results in the modelling and analysis of linearly additive spatially invariant image sequences are based on the inherent structure of such images, and can be used to achieve significant data compression for image storage and still provide good reconstruction. The technique is applied here to a human renogram, with compression of a very noisy 180-image sequence to a 4-image set. The resulting reconstruction illustrates the potential of the method.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.