14 research outputs found
Beam Orientation Optimization for Intensity Modulated Radiation Therapy using Adaptive l1 Minimization
Beam orientation optimization (BOO) is a key component in the process of IMRT
treatment planning. It determines to what degree one can achieve a good
treatment plan quality in the subsequent plan optimization process. In this
paper, we have developed a BOO algorithm via adaptive l_1 minimization.
Specifically, we introduce a sparsity energy function term into our model which
contains weighting factors for each beam angle adaptively adjusted during the
optimization process. Such an energy term favors small number of beam angles.
By optimizing a total energy function containing a dosimetric term and the
sparsity term, we are able to identify the unimportant beam angles and
gradually remove them without largely sacrificing the dosimetric objective. In
one typical prostate case, the convergence property of our algorithm, as well
as the how the beam angles are selected during the optimization process, is
demonstrated. Fluence map optimization (FMO) is then performed based on the
optimized beam angles. The resulted plan quality is presented and found to be
better than that obtained from unoptimized (equiangular) beam orientations. We
have further systematically validated our algorithm in the contexts of 5-9
coplanar beams for 5 prostate cases and 1 head and neck case. For each case,
the final FMO objective function value is used to compare the optimized beam
orientations and the equiangular ones. It is found that, our BOO algorithm can
lead to beam configurations which attain lower FMO objective function values
than corresponding equiangular cases, indicating the effectiveness of our BOO
algorithm.Comment: 19 pages, 2 tables, and 5 figure
GPU-based Fast Low-dose Cone Beam CT Reconstruction via Total Variation
Cone-beam CT (CBCT) has been widely used in image guided radiation therapy
(IGRT) to acquire updated volumetric anatomical information before treatment
fractions for accurate patient alignment purpose. However, the excessive x-ray
imaging dose from serial CBCT scans raises a clinical concern in most IGRT
procedures. The excessive imaging dose can be effectively reduced by reducing
the number of x-ray projections and/or lowering mAs levels in a CBCT scan. The
goal of this work is to develop a fast GPU-based algorithm to reconstruct high
quality CBCT images from undersampled and noisy projection data so as to lower
the imaging dose. The CBCT is reconstructed by minimizing an energy functional
consisting of a data fidelity term and a total variation regularization term.
We developed a GPU-friendly version of the forward-backward splitting algorithm
to solve this model. A multi-grid technique is also employed. We test our CBCT
reconstruction algorithm on a digital NCAT phantom and a head-and-neck patient
case. The performance under low mAs is also validated using a physical Catphan
phantom and a head-and-neck Rando phantom. It is found that 40 x-ray
projections are sufficient to reconstruct CBCT images with satisfactory quality
for IGRT patient alignment purpose. Phantom experiments indicated that CBCT
images can be successfully reconstructed with our algorithm under as low as 0.1
mAs/projection level. Comparing with currently widely used full-fan
head-and-neck scanning protocol of about 360 projections with 0.4
mAs/projection, it is estimated that an overall 36 times dose reduction has
been achieved with our algorithm. Moreover, the reconstruction time is about
130 sec on an NVIDIA Tesla C1060 GPU card, which is estimated ~100 times faster
than similar iterative reconstruction approaches.Comment: 20 pages, 10 figures, Paper was revised and more testing cases were
added
Four-dimensional Cone Beam CT Reconstruction and Enhancement using a Temporal Non-Local Means Method
Four-dimensional Cone Beam Computed Tomography (4D-CBCT) has been developed
to provide respiratory phase resolved volumetric imaging in image guided
radiation therapy (IGRT). Inadequate number of projections in each phase bin
results in low quality 4D-CBCT images with obvious streaking artifacts. In this
work, we propose two novel 4D-CBCT algorithms: an iterative reconstruction
algorithm and an enhancement algorithm, utilizing a temporal nonlocal means
(TNLM) method. We define a TNLM energy term for a given set of 4D-CBCT images.
Minimization of this term favors those 4D-CBCT images such that any anatomical
features at one spatial point at one phase can be found in a nearby spatial
point at neighboring phases. 4D-CBCT reconstruction is achieved by minimizing a
total energy containing a data fidelity term and the TNLM energy term. As for
the image enhancement, 4D-CBCT images generated by the FDK algorithm are
enhanced by minimizing the TNLM function while keeping the enhanced images
close to the FDK results. A forward-backward splitting algorithm and a
Gauss-Jacobi iteration method are employed to solve the problems. The
algorithms are implemented on GPU to achieve a high computational efficiency.
The reconstruction algorithm and the enhancement algorithm generate visually
similar 4D-CBCT images, both better than the FDK results. Quantitative
evaluations indicate that, compared with the FDK results, our reconstruction
method improves contrast-to-noise-ratio (CNR) by a factor of 2.56~3.13 and our
enhancement method increases the CNR by 2.75~3.33 times. The enhancement method
also removes over 80% of the streak artifacts from the FDK results. The total
computation time is ~460 sec for the reconstruction algorithm and ~610 sec for
the enhancement algorithm on an NVIDIA Tesla C1060 GPU card.Comment: 20 pages, 3 figures, 2 table
GPU-based Iterative Cone Beam CT Reconstruction Using Tight Frame Regularization
X-ray imaging dose from serial cone-beam CT (CBCT) scans raises a clinical
concern in most image guided radiation therapy procedures. It is the goal of
this paper to develop a fast GPU-based algorithm to reconstruct high quality
CBCT images from undersampled and noisy projection data so as to lower the
imaging dose. For this purpose, we have developed an iterative tight frame (TF)
based CBCT reconstruction algorithm. A condition that a real CBCT image has a
sparse representation under a TF basis is imposed in the iteration process as
regularization to the solution. To speed up the computation, a multi-grid
method is employed. Our GPU implementation has achieved high computational
efficiency and a CBCT image of resolution 512\times512\times70 can be
reconstructed in ~5 min. We have tested our algorithm on a digital NCAT phantom
and a physical Catphan phantom. It is found that our TF-based algorithm is able
to reconstrct CBCT in the context of undersampling and low mAs levels. We have
also quantitatively analyzed the reconstructed CBCT image quality in terms of
modulation-transfer-function and contrast-to-noise ratio under various scanning
conditions. The results confirm the high CBCT image quality obtained from our
TF algorithm. Moreover, our algorithm has also been validated in a real
clinical context using a head-and-neck patient case. Comparisons of the
developed TF algorithm and the current state-of-the-art TV algorithm have also
been made in various cases studied in terms of reconstructed image quality and
computation efficiency.Comment: 24 pages, 8 figures, accepted by Phys. Med. Bio
Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples
Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts
Optimization of Process Parameters and Analysis of Microstructure and Properties of 18Ni300 by Selective Laser Melting
In this research, we studied the influence of process parameters on the quality of selective laser melting of 18Ni300 maraging steel. The effects of laser power and scanning speed on the relative density and hardness of 18Ni300 were studied by single-factor experiment and the orthogonal experimental method. The relative optimal process parameters of 18Ni300 were obtained when the layer thickness was 0.03 mm, and the hatch space was 0.1 mm. The microstructures and mechanical properties of the samples formed under different process parameters were characterized. The results showed that the optimal hardness and relative density of the sample were 44.7 HRC and 99.98% when the laser power was 230 W and the scanning speed was 1100 mm/s, respectively; the microstructure of the material was uniform and dense, exhibiting few pores. Some columnar crystals appeared along the boundary of the molten pool due to vertical epitaxial growth. The orientation of fine grains at the boundary of the molten pool was random, and some coarse columnar crystals in the molten pool exhibited a certain orientational preference along the <001> orientation. In the case of optimal process parameters, the SLM-formed 18Ni300 was composed of 99.5% martensite and 0.5% retained austenite; the indentation hardness was distributed in the range of 3.2–5 GPa. The indentation modulus was between 142.8–223.4 GPa, exhibiting stronger fluctuations than the indentation hardness. The sample’s mechanical properties showed obvious anisotropy, while the tensile fracture characteristics exhibited necking. The tensile fracture morphology was ductile, and large equiaxed dimples and holes could be observed in the fiber area, accompanied by tearing characteristics
Synthesis of Fe2+ Substituted High-Performance LiMn1−xFexPO4/C (x = 0, 0.1, 0.2, 0.3, 0.4) Cathode Materials for Lithium-Ion Batteries via Sol-Gel Processes
A series of carbon-coated LiMn1−xFexPO4 (x = 0, 0.1, 0.2, 0.3, 0.4) materials are successfully constructed using glucose as carbon sources via sol-gel processes. The morphology of the synthesized material particles are more regular and particle sizes are more homogeneous. The carbon-coated LiMn0.8Fe0.2PO4 material obtains the discharge specific capacity of 152.5 mAh·g−1 at 0.1 C rate and its discharge specific capacity reaches 95.7 mAh·g−1 at 5 C rate. Iron doping offers a viable way to improve the electronic conductivity and lattice defects of materials, as well as improving transmission kinetics, thereby improving the rate performance and cycle performance of materials, which is an effective method to promote the electrical properties