scholarly journals High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Manob Jyoti Saikia ◽  
Rajan Kanhirodan ◽  
Ram Mohan Vasu

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second.

2018 ◽  
Vol 11 (4) ◽  
pp. 313-325
Author(s):  
Farshad Zamiri ◽  
Abdolreza Nabavi

AbstractMicrowave holography technique reconstructs a target image using recorded amplitudes and phases of the signals reflected from the target with Fast Fourier Transform (FFT)-based algorithms. The reconstruction algorithms have two or more steps of two- and three-dimensional Fourier transforms, which have a high computational load. In this paper, by neglecting the impact of target depth on image reconstruction, an efficient Fresnel-based algorithm is proposed, involving only one-step FFT for both single- and multi-frequency microwave imaging. Numerous tests have been performed to show the effectiveness of the proposed algorithm including planar and non-planar targets, using the raw data gathered by means of a scanner operating in X-band. Finally, a low-cost and high-speed hardware architecture based on fixed-point arithmetic is introduced which reconstructs the planar targets. This pipeline architecture was tested on field programmable gate arrays operating at 200 MHz clock frequency, which illustrates more than 30 times improvement in computation time compared with a computer.


Author(s):  
Robert W. Mackin

This paper presents two advances towards the automated three-dimensional (3-D) analysis of thick and heavily-overlapped regions in cytological preparations such as cervical/vaginal smears. First, a high speed 3-D brightfield microscope has been developed, allowing the acquisition of image data at speeds approaching 30 optical slices per second. Second, algorithms have been developed to detect and segment nuclei in spite of the extremely high image variability and low contrast typical of such regions. The analysis of such regions is inherently a 3-D problem that cannot be solved reliably with conventional 2-D imaging and image analysis methods.High-Speed 3-D imaging of the specimen is accomplished by moving the specimen axially relative to the objective lens of a standard microscope (Zeiss) at a speed of 30 steps per second, where the stepsize is adjustable from 0.2 - 5μm. The specimen is mounted on a computer-controlled, piezoelectric microstage (Burleigh PZS-100, 68/μm displacement). At each step, an optical slice is acquired using a CCD camera (SONY XC-11/71 IP, Dalsa CA-D1-0256, and CA-D2-0512 have been used) connected to a 4-node array processor system based on the Intel i860 chip.


2021 ◽  
Author(s):  
Scott J. Peltier ◽  
Brian E. Rice ◽  
Ethan Johnson ◽  
Venkateswaran Narayanaswamy ◽  
Marvin E. Sellers

2018 ◽  
Author(s):  
Yi Chen Mazumdar ◽  
Michael E. Smyser ◽  
Jeffery Dean Heyborne ◽  
Daniel Robert Guildenbecher

2019 ◽  
Vol 13 (2) ◽  
pp. 174-180
Author(s):  
Poonam Sharma ◽  
Ashwani Kumar Dubey ◽  
Ayush Goyal

Background: With the growing demand of image processing and the use of Digital Signal Processors (DSP), the efficiency of the Multipliers and Accumulators has become a bottleneck to get through. We revised a few patents on an Application Specific Instruction Set Processor (ASIP), where the design considerations are proposed for application-specific computing in an efficient way to enhance the throughput. Objective: The study aims to develop and analyze a computationally efficient method to optimize the speed performance of MAC. Methods: The work presented here proposes the design of an Application Specific Instruction Set Processor, exploiting a Multiplier Accumulator integrated as the dedicated hardware. This MAC is optimized for high-speed performance and is the application-specific part of the processor; here it can be the DSP block of an image processor while a 16-bit Reduced Instruction Set Computer (RISC) processor core gives the flexibility to the design for any computing. The design was emulated on a Xilinx Field Programmable Gate Array (FPGA) and tested for various real-time computing. Results: The synthesis of the hardware logic on FPGA tools gave the operating frequencies of the legacy methods and the proposed method, the simulation of the logic verified the functionality. Conclusion: With the proposed method, a significant improvement of 16% increase in throughput has been observed for 256 steps iterations of multiplier and accumulators on an 8-bit sample data. Such an improvement can help in reducing the computation time in many digital signal processing applications where multiplication and addition are done iteratively.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiang Lan Fan ◽  
Jose A. Rivera ◽  
Wei Sun ◽  
John Peterson ◽  
Henry Haeberle ◽  
...  

AbstractUnderstanding the structure and function of vasculature in the brain requires us to monitor distributed hemodynamics at high spatial and temporal resolution in three-dimensional (3D) volumes in vivo. Currently, a volumetric vasculature imaging method with sub-capillary spatial resolution and blood flow-resolving speed is lacking. Here, using two-photon laser scanning microscopy (TPLSM) with an axially extended Bessel focus, we capture volumetric hemodynamics in the awake mouse brain at a spatiotemporal resolution sufficient for measuring capillary size and blood flow. With Bessel TPLSM, the fluorescence signal of a vessel becomes proportional to its size, which enables convenient intensity-based analysis of vessel dilation and constriction dynamics in large volumes. We observe entrainment of vasodilation and vasoconstriction with pupil diameter and measure 3D blood flow at 99 volumes/second. Demonstrating high-throughput monitoring of hemodynamics in the awake brain, we expect Bessel TPLSM to make broad impacts on neurovasculature research.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3652
Author(s):  
Cory Juntunen ◽  
Isabel M. Woller ◽  
Yongjin Sung

Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection optical tomography (SPOT) and Fourier-transform spectroscopy (FTS). SPOT allows us to instantaneously acquire the projection images corresponding to different viewing angles, while FTS allows us to perform hyperspectral imaging at high spectral resolution. Using fluorescent beads and sunflower pollens, we demonstrate the imaging performance of the developed system.


2021 ◽  
Vol 13 (5) ◽  
pp. 2950
Author(s):  
Su-Kyung Sung ◽  
Eun-Seok Lee ◽  
Byeong-Seok Shin

Climate change increases the frequency of localized heavy rains and typhoons. As a result, mountain disasters, such as landslides and earthworks, continue to occur, causing damage to roads and residential areas downstream. Moreover, large-scale civil engineering works, including dam construction, cause rapid changes in the terrain, which harm the stability of residential areas. Disasters, such as landslides and earthenware, occur extensively, and there are limitations in the field of investigation; thus, there are many studies being conducted to model terrain geometrically and to observe changes in terrain according to external factors. However, conventional topography methods are expressed in a way that can only be interpreted by people with specialized knowledge. Therefore, there is a lack of consideration for three-dimensional visualization that helps non-experts understand. We need a way to express changes in terrain in real time and to make it intuitive for non-experts to understand. In conventional height-based terrain modeling and simulation, there is a problem in which some of the sampled data are irregularly distorted and do not show the exact terrain shape. The proposed method utilizes a hierarchical vertex cohesion map to correct inaccurately modeled terrain caused by uniform height sampling, and to compensate for geometric errors using Hausdorff distances, while not considering only the elevation difference of the terrain. The mesh reconstruction, which triangulates the three-vertex placed at each location and makes it the smallest unit of 3D model data, can be done at high speed on graphics processing units (GPUs). Our experiments confirm that it is possible to express changes in terrain accurately and quickly compared with existing methods. These functions can improve the sustainability of residential spaces by predicting the damage caused by mountainous disasters or civil engineering works around the city and make it easy for non-experts to understand.


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