23,576 research outputs found
A Multi-Grid Iterative Method for Photoacoustic Tomography
Inspired by the recent advances on minimizing nonsmooth or bound-constrained
convex functions on models using varying degrees of fidelity, we propose a line
search multigrid (MG) method for full-wave iterative image reconstruction in
photoacoustic tomography (PAT) in heterogeneous media. To compute the search
direction at each iteration, we decide between the gradient at the target
level, or alternatively an approximate error correction at a coarser level,
relying on some predefined criteria. To incorporate absorption and dispersion,
we derive the analytical adjoint directly from the first-order acoustic wave
system. The effectiveness of the proposed method is tested on a total-variation
penalized Iterative Shrinkage Thresholding algorithm (ISTA) and its accelerated
variant (FISTA), which have been used in many studies of image reconstruction
in PAT. The results show the great potential of the proposed method in
improving speed of iterative image reconstruction
Real-time diffuse optical tomography using reduced-order light propagation models based on a priori anatomical and functional information
This paper proposes a new fast 3D image reconstruction
algorithm for Diffuse Optical Tomography using reduced
order polynomial mappings from the space of optical
tissue parameters into the space of flux measurements at
the detector locations. The polynomial mappings are
constructed through an iterative estimation process
involving structure detection, parameter estimation and
cross-validation using data generated by simulating a
diffusion approximation of the radiative transfer equation
incorporating a priori anatomical and functional
information provided by MR scans and prior psychological
evidence. Numerical simulation studies demonstrate that
reconstructed images are remarkably similar in quality as
those obtained using the standard approach, but obtained at
a fraction of the time
Similarity Search Over Graphs Using Localized Spectral Analysis
This paper provides a new similarity detection algorithm. Given an input set
of multi-dimensional data points, where each data point is assumed to be
multi-dimensional, and an additional reference data point for similarity
finding, the algorithm uses kernel method that embeds the data points into a
low dimensional manifold. Unlike other kernel methods, which consider the
entire data for the embedding, our method selects a specific set of kernel
eigenvectors. The eigenvectors are chosen to separate between the data points
and the reference data point so that similar data points can be easily
identified as being distinct from most of the members in the dataset.Comment: Published in SampTA 201
Improved neighbor list algorithm in molecular simulations using cell decomposition and data sorting method
An improved neighbor list algorithm is proposed to reduce unnecessary
interatomic distance calculations in molecular simulations. It combines the
advantages of Verlet table and cell linked list algorithms by using cell
decomposition approach to accelerate the neighbor list construction speed, and
data sorting method to lower the CPU data cache miss rate, as well as partial
updating method to minimize the unnecessary reconstruction of the neighbor
list. Both serial and parallel performance of molecular dynamics simulation are
evaluated using the proposed algorithm and compared with those using
conventional Verlet table and cell linked list algorithms. Results show that
the new algorithm outperforms the conventional algorithms by a factor of 2~3 in
cases of both small and large number of atoms.Comment: 14 pages, 7 figures. Submitted to Computer Physics Communication
Whole-brain vasculature reconstruction at the single capillary level
The distinct organization of the brain’s vascular network ensures that it is adequately supplied with oxygen and nutrients. However, despite this fundamental role, a detailed reconstruction of the brain-wide vasculature at the capillary level remains elusive, due to insufficient image quality using the best available techniques. Here, we demonstrate a novel approach that improves vascular demarcation by combining CLARITY with a vascular staining approach that can fill the entire blood vessel lumen and imaging with light-sheet fluorescence microscopy. This method significantly improves image contrast, particularly in depth, thereby allowing reliable application of automatic segmentation algorithms, which play an increasingly important role in high-throughput imaging of the terabyte-sized datasets now routinely produced. Furthermore, our novel method is compatible with endogenous fluorescence, thus allowing simultaneous investigations of vasculature and genetically targeted neurons. We believe our new method will be valuable for future brain-wide investigations of the capillary network
A comparative study of breast surface reconstruction for aesthetic outcome assessment
Breast cancer is the most prevalent cancer type in women, and while its
survival rate is generally high the aesthetic outcome is an increasingly
important factor when evaluating different treatment alternatives. 3D scanning
and reconstruction techniques offer a flexible tool for building detailed and
accurate 3D breast models that can be used both pre-operatively for surgical
planning and post-operatively for aesthetic evaluation. This paper aims at
comparing the accuracy of low-cost 3D scanning technologies with the
significantly more expensive state-of-the-art 3D commercial scanners in the
context of breast 3D reconstruction. We present results from 28 synthetic and
clinical RGBD sequences, including 12 unique patients and an anthropomorphic
phantom demonstrating the applicability of low-cost RGBD sensors to real
clinical cases. Body deformation and homogeneous skin texture pose challenges
to the studied reconstruction systems. Although these should be addressed
appropriately if higher model quality is warranted, we observe that low-cost
sensors are able to obtain valuable reconstructions comparable to the
state-of-the-art within an error margin of 3 mm.Comment: This paper has been accepted to MICCAI201
Morphological study of skin cancer lesions through a 3D scanner based on fringe projection and machine learning
Postprint (published version
- …