Tag: x-ray imaging

GPU-Accelerated 3D Volumetric X-Ray-Induced Acoustic Computed Tomography

Author(s): Donghyun Lee, Eun-Yeong Park, Seongwook Choi, Hyeongsub Kim, Jung-joon Min, Changho Lee, and Chulhong Kim ABSTRACT X-ray acoustic imaging is a hybrid biomedical imaging technique that can acoustically monitor X-ray absorption distribution in biological tissues through the X-ray induced acoustic effect. In this study, we developed a 3D volumetric X-ray-induced acoustic computed tomography (XACT) […]

Discrete Wavelet Transformation for the Sensitive Detection of Ultrashort Radiation Pulse with Radiation-Induced Acoustics

Authors: Rick Van Bergen, Leshan Sun, Prabodh Kumar Pandey, Siqi Wang, Kristina Bjegovic, Gilberto Gonzalez, Yong Chen, Richard Lopata, Liangzhong Xiang ABSTRACT Radiation-induced acoustics (RIA) shows promise in advancing radiological imaging and radiotherapy dosimetry methods. However, RIA signals often require extensive averaging to achieve reasonable signal-to-noise ratios, which increases patient radiation exposure and limits real-time […]

X-Ray Acoustics

PhotoSounds OEM line of products is an ideal starting point for the development of custom systems where the parallel acquisition of multiple channels is required. All our ADCs are streaming and allow the continuous acquisition of data straight to the receiving computer for processing or storage. PhotoSound’s ADCs are feature-rich, they have multiple electronic and […]

REAL-TIME PHOTOACOUSTIC DATA ACQUISITION WITH A THOUSAND PARALLEL CHANNELS AT HUNDREDS FRAMES PER SECOND

Authors: Vassili Ivanov, Hans Peter Brecht, Sergey A. Ermilov AFFILIATIONS PhotoSound Technologies, Inc. (United States) ABSTRACT Large number of simultaneously acquired spatially distinct pressure signals is required to improve quality of real-time photoacoustic and x-ray acoustic biomedical images [1]. In the past this approach was limited by availability of commercial multi-channel analog-to-digital converter (ADC) systems […]

RADIATION-INDUCED ACOUSTIC SIGNAL DENOISING USING A SUPERVISED DEEP LEARNING FRAMEWORK FOR IMAGING AND THERAPY MONITORING

Author(s): Zhuoran Jiang, Siqi Wang, Yifei Xu, Leshan Sun, Gilberto Gonzalez, Yong Chen, Q. Jackie Wu, Liangzhong Xiang, Lei Ren​ ABSTRACT Radiation-induced acoustic (RA) imaging is a promising technique for visualizing radiation energy deposition in tissues, enabling new imaging modalities and real-time therapy monitoring. However, it requires measuring hundreds or even thousands of averages to achieve satisfactory signal-to-noise ratios (SNRs). This repetitive […]