Imaging technology

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

Three-Dimensional Voxel-Level Classification of Ultrasound Scattering

Abstract: Three-dimensional (3D) H-scan ultrasound (US) is a new high-resolution imaging technology for voxel-level tissue classification. For the purpose of validation, a simulated H-scan US imaging system was developed to comprehensively study the sensitivity to scatterer size in volume space. A programmable research US system (Vantage 256, Verasonics Inc, Kirkland, WA) equipped with a custom volumetric imaging transducer (4DL7, Vermon, Tours, France) was used for US data acquisition and comparison to simulated findings. Preliminary studies were conducted using homogeneous phantoms embedded with acoustic scatterers of varying sizes (15, 30, 40 or 250 μm). Both simulation and experimental results indicate that the H -scan US imaging method is more sensitive than B-mode US in differentiating US scatterers of varying size. Overall, this study proved useful for evaluating H -scan US imaging of tissue scatterer patterns and will inform future technology research and development.

Deep imaging technology needed for NIH BRAIN initiative

Abstract: This opinion piece discusses potential funding opportunities by the NIH BRAIN initiative to support the development of deep imaging technologies.

New image processing challenges for jointly designed electro-optical imaging systems

Abstract: Still-image processing algorithms are tailored to and depend crucially upon the properties of the class of images to which they are applied, for instance natural images in consumer digital cameras, medical images in fMRI machines, and binary text images in some photocopiers. We describe a new and possibly very important class of images and tasks for which traditional algorithms seem ill-suited, and for which new algorithms and general methods and concepts are required. This new class of images arises in imaging systems designed through new, joint optimization methods where the optics and the image processing are designed simultaneously in order to yield a high-quality digital image. These new design methods yield intermediate optical images that have unusual spatial, noise and chromatic properties ill-served by traditional image methods. Moreover, these new images present a number of novel challenges in image processing hardware implementations such as constrained space-variance. We describe these briefly new, joint methods for designing digital-optical imaging systems, characterize the intermediate optical images they yield, and some of the digital image processing challenges for producing high-quality still images from these sensed optical images.

Application of machine learning method in optical molecular imaging: a review

Abstract: Optical molecular imaging (OMI) is an imaging technology that uses an optical signal, such as near-infrared light, to detect biological tissue in organisms. Because of its specific and sensitive imaging performance, it is applied in both preclinical research and clinical surgery. However, it requires heavy data analysis and a complex mathematical model of tomographic imaging. In recent years, machine learning (ML)-based artificial intelligence has been used in different fields because of its ability to perform powerful data processing. Its analytical capability for processing complex and large data provides a feasible scheme for the requirement of OMI. In this paper, we review ML-based methods applied in different OMI modalities.

Review of Polarization Imaging Technology for International Military Application(II)

Abstract: Polarization imaging, as a new photoelectric detection technology, has unique advantage in target detection, recognition and processing compared with traditional imaging technology. Polarization imaging has great potential and important significance in the future wars with complex battlefield environment. In this paper, the research and application of polarization imaging and detection in the military field in recent years are reviewed in four areas as material polarization characteristics, polarization transmission characteristics, polarization detection equipment, polarization information processing etc. This paper, as the second part of the thesis, focus on ①detection method for polarization imaging, being used to detect target, acquire polarization information and improve the imaging quality; ②polarization information processing, being used to improve the detection probability, reducing false alarm rate.