Accelerating frequency-domain diffuse optical tomographic image reconstruction using graphics processing units

Diffuse optical tomographic image reconstruction uses advanced numerical models that are computationally costly to be implemented in the real time. The graphics processing units (GPUs) offer desktop massive parallelization that can accelerate these computations. An open-source GPU-accelerated linear algebra library package is used to compute the most intensive matrix-matrix calculations and matrix decompositions that are used in solving the system of linear equations. These open-source functions were integrated into the existing frequency-domain diffuse optical image reconstruction algorithms to evaluate the acceleration capability of the GPUs (NVIDIA Tesla C 1060) with increasing reconstruction problem sizes. These studies indicate that single precision computations are sufficient for diffuse optical tomographic image reconstruction. The acceleration per iteration can be up to 40, using GPUs compared to traditional CPUs in case of three-dimensional reconstruction, where the reconstruction problem is more underdetermined, making the GPUs more attractive in the clinical settings. The current limitation of these GPUs in the available onboard memory (4 GB) that restricts the reconstruction of a large set of optical parameters, more than 13, 377. (C) 2010 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.3506216]

Understanding changes in the Himalayan cryosphere using remote sensing techniques

In the Himalayas, a large area is covered by glaciers and seasonal snow and changes in its extent can influence availability of water in the Himalayan Rivers. In this paper, changes in glacial extent, glacial mass balance and seasonal snow cover are discussed. Glacial retreat was estimated for 1868 glaciers in 11 basins distributed in the Indian Himalaya since 1962. The investigation has shown an overall reduction in glacier area from 6332 to 5329km2 from 1962 to 2001/2 - an overall deglaciation of 16%. Snow line at the end of ablation season on the Chhota Shigri glacier observed using field and satellite methods suggests a change in altitude from 4900 to 5200m from the late 1970s to present. Seasonal snow cover was monitored in the 28 river sub-basins using normalized difference snow index (NDSI) technique in Central and Western Himalaya. The investigation has shown that in the early part of winter, i.e. from October to December, a large amount of snow retreat was observed. For many basins located in lower altitude and in the south of the Pir Panjal range, snow ablation was observed throughout the winter season. In addition, average stream runoff of the Baspa basin for the month of December increased by 75%. This combination of glacial retreat, negative mass balance, early melting of seasonal snow cover and winter-time increase in stream runoff might suggest an influence of global warming on the Himalayan cryosphere.

Fiber Bragg Grating Sensors for Real Time Monitoring of Evacuation Process

Fiber bragg grating (FBG) sensors have been widely used for number of sensing applications like temperature, pressure, acousto-ultrasonic, static and dynamic strain, refractive index change measurements and so on. Present work demonstrates the use of FBG sensors in in-situ measurement of vacuum process with simultaneous leak detection capability. Experiments were conducted in a bell jar vacuum chamber facilitated with conventional Pirani gauge for vacuum measurement. Three different experiments have been conducted to validate the performance of FBG sensor in monitoring vacuum creating process and air bleeding. The preliminary results of FBG sensors in vacuum monitoring have been compared with that of commercial Pirani gauge sensor. This novel technique offers a simple alternative to conventional method for real time monitoring of evacuation process. Proposed FBG based vacuum sensor has potential applications in vacuum systems involving hazardous environment such as chemical and gas plants, automobile industries, aeronautical establishments and leak monitoring in process industries, where the electrical or MEMS based sensors are prone to explosion and corrosion.

Accelerated gradient based diffuse optical tomographic image reconstruction

Purpose: Fast reconstruction of interior optical parameter distribution using a new approach called Broyden-based model iterative image reconstruction (BMOBIIR) and adjoint Broyden-based MOBIIR (ABMOBIIR) of a tissue and a tissue mimicking phantom from boundary measurement data in diffuse optical tomography (DOT). Methods: DOT is a nonlinear and ill-posed inverse problem. Newton-based MOBIIR algorithm, which is generally used, requires repeated evaluation of the Jacobian which consumes bulk of the computation time for reconstruction. In this study, we propose a Broyden approach-based accelerated scheme for Jacobian computation and it is combined with conjugate gradient scheme (CGS) for fast reconstruction. The method makes explicit use of secant and adjoint information that can be obtained from forward solution of the diffusion equation. This approach reduces the computational time many fold by approximating the system Jacobian successively through low-rank updates. Results: Simulation studies have been carried out with single as well as multiple inhomogeneities. Algorithms are validated using an experimental study carried out on a pork tissue with fat acting as an inhomogeneity. The results obtained through the proposed BMOBIIR and ABMOBIIR approaches are compared with those of Newton-based MOBIIR algorithm. The mean squared error and execution time are used as metrics for comparing the results of reconstruction. Conclusions: We have shown through experimental and simulation studies that Broyden-based MOBIIR and adjoint Broyden-based methods are capable of reconstructing single as well as multiple inhomogeneities in tissue and a tissue-mimicking phantom. Broyden MOBIIR and adjoint Broyden MOBIIR methods are computationally simple and they result in much faster implementations because they avoid direct evaluation of Jacobian. The image reconstructions have been carried out with different initial values using Newton, Broyden, and adjoint Broyden approaches. These algorithms work well when the initial guess is close to the true solution. However, when initial guess is far away from true solution, Newton-based MOBIIR gives better reconstructed images. The proposed methods are found to be stable with noisy measurement data. (C) 2011 American Association of Physicists in Medicine. DOI: 10.1118/1.3531572]