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To investigate the concept of filling the air gaps of the conventional contrast detail phantom (CDP) with various concentrations of contrast media, and to develop a variable level of attenuation-level differential phantoms that could be more appropriate for contrast measurements in some radiology cases.
Image-guided radiation therapy (IGRT) through daily cone-beam computed tomography (CBCT) has significantly impacted the role of the radiation therapist at our institution; continuing education is crucial to ensure safe practice of technology in the clinical environment. The purpose of this work was to develop and implement an electronic learning (eLearning) module as a yearly refresher for CBCT-practicing radiation therapists.
Complexity and scale of next generation HPC systems pose significant challenges in fault resilience methods such that contemporary checkpoint/restart (C/R) methods that address fail-stop behavior may be insufficient. Redundant computing has been proposed as an alternative at extreme scale. Triple redundancy has an advantage over C/R in that it can also detect silent data corruption (SDC) and then correct results via voting. However, current redundant computing approaches do not repair failed or corrupted replicas. Consequently, SDCs can no longer be detected after a replica failure since the system has been degraded to dual redundancy without voting capability. Hence, a job may have to be aborted if voting uncovers mismatching results between the remaining two replicas. And while replicas are logically equivalent, they may have divergent runtime states during job execution, which presents a challenge to simply creating new replicas dynamically. This problem is addressed by, DIvergent NOde cloning (DINO), a redundant execution environment that quickly recovers from hard failures. DINO consists of a novel node cloning service integrated into the MPI runtime system that solves the problem of consolidating divergent states among replicas on-the-fly. With DINO, after degradation to dual redundancy, a good replica can be quickly cloned so that triple redundancy is restored. We present experimental results over 9 NAS Parallel Benchmarks (NPB), Sweep3D and LULESH. Results confirm the applicability of the approach and the correctness of the recovery process and indicate that DINO can recover from failures nearly instantly. The cloning overhead depends on the process image size that needs to be transferred between source and destination of the clone operation and varies between 5.60 to 90.48 s. Here, simulation results with our model show that dual redundancy with DINO recovery always outperforms 2x and surpasses 3x redundancy on up to 1 million nodes. To the best of our knowledge, the design and implementation for repairing failed replicas in redundant MPI computing is unprecedented.
This paper introduces an improved method for the detailed geometrical characterization of perlite-metal syntactic foam. This novel metallic foam is created by infiltrating a packed bed of expanded perlite particles with liquid aluminium alloy. The geometry of the solidified metal is thus defined by the perlite particle shape, size and morphology. The method is based on a segmented micro-computed tomography data and allows for automated determination of the distributions of pore size, sphericity, orientation and location. The pore (i.e. particle) size distribution and pore orientation is determined by a multi-criteria k-nearest neighbour algorithm for pore identification. The results indicate a weak density gradient parallel to the casting direction and a slight preference of particle orientation perpendicular to the casting direction. - Highlights: •A new method for identification of pores in porous materials was developed. •It was applied on perlite-metal syntactic foam samples. •A porosity decrease in the axial direction of the samples was determined. •Pore shape analysis showed a high percentage of spherical pores. •Orientation analysis showed that more pores are oriented in the radial direction.
During the firing of bricks, mineralogical and textural transformations produce an artificial aggregate characterised by significant porosity. Particularly as regards pore-size distribution and the interconnection model, porosity is an important parameter to evaluate and predict the durability of bricks. The pore system is in fact the main element, which correlates building materials and their environment (especially in cases of aggressive weathering, e.g., salt crystallisation and freeze-thaw cycles) and determines their durability. Four industrial bricks with differing compositions and firing temperatures were analysed with “direct” and “indirect” techniques, traditional methods (mercury intrusion porosimetry, hydric tests, nitrogen adsorption) and new analytical approaches based on digital image reconstruction of 2D and 3D models (back-scattered electrons and computerised X-ray micro-Tomography, respectively). The comparison of results from different analytical methods in the “overlapping ranges” of porosity and the careful reconstruction of a cumulative curve, allowed overcoming their specific limitations and achieving better knowledge on the pore system of bricks. - Highlights: •Pore-size distribution and structure of the pore system in four commercial bricks •A multi-analytical approach combining “direct” and “indirect” techniques •Traditional methods vs. new approaches based on 2D/3D digital image reconstruction •The use of “overlapping ranges” to overcome the limitations of various techniques.
The present research was aimed at gaining an understanding of the porous structure changes from the green body through water leaching and sintering to titanium scaffolds. Micro-computed tomography (micro-CT) was performed to generate 3D models of titanium scaffold preforms containing carbamide space-holding particles and sintered scaffolds containing macro- and micro-pores. The porosity values and structural parameters were determined by means of image analysis. The result showed that the porosity values, macro-pore sizes, connectivity densities and specific surface areas of the titanium scaffolds sintered at 1200 °C for 3 h did not significantly deviate from those of the green structures with various volume fractions of the space holder. Titanium scaffolds with a maximum specific surface area could be produced with an addition of 60–65 vol% carbamide particles to the matrix powder. The connectivity of pores inside the scaffold increased with rising volume fraction of the space holder. The shrinkage of the scaffolds prepared with > 50 vol% carbamide space holder, occurring during sintering, was caused by the reductions of macro-pore sizes and micro-pore sizes as well as the thickness of struts. In conclusion, the final porous structural characteristics of titanium scaffolds could be estimated from those of the green body. - Highlights: •Porous structures of green body and sintered titanium scaffolds was studied. •Porous structures of both samples were quantitatively characterized with micro-CT. •Porous structures of scaffolds could be controlled from the green body. •Shrinkage mechanisms of titanium scaffolds during sintering was established.
Several publications have recommended that patients undergoing whole-breast radiotherapy be resimulated for boost planning. The rationale for this is that the seroma may be smaller when compared with the initial simulation. However, the decision remains whether to use the earlier or later images to define an appropriate boost target volume. A patient undergoing whole-breast radiotherapy had new, injectable, temporary hydrogel fiducial markers placed 1 to 3 cm from the seroma at the time of initial simulation. The patient was resimulated 4.5 weeks later for conformal photon boost planning. Computed tomography (CT) scans acquired at the beginning and the end of whole-breast radiotherapy showed that shrinkage of the lumpectomy cavity was not matched by a corresponding reduction in the surrounding tissue volume, as demarcated by hydrogel markers. This observation called into question the usual interpretation of cavity shrinkage for boost target definition. For this patient, it was decided to define the boost target volume on the initial planning CT instead of the new CT.
There is a reduction in cardiac dose for left-sided breast radiotherapy during treatment with deep inspiration breath-hold (DIBH) when compared with treatment with free breathing (FB). Various levels of DIBH may occur for different treatment fractions. Dosimetric effects due to this and other motions are a major component of uncertainty in radiotherapy in this setting. Recent developments in deformable registration techniques allow displacement vectors between various temporal and spatial patient representations to be digitally quantified. We propose a method to evaluate the dosimetric effect to the heart from variable reproducibility of DIBH by using deformable registration to create new anatomical computed tomography (CT) scans. From deformable registration, 3-dimensional deformation vectors are generated with FB and DIBH. The obtained deformation vectors are scaled to 75%, 90%, and 110% and are applied to the reference image to create new CT scans at these inspirational levels. The scans are then imported into the treatment planning system and dose calculations are performed. The average mean dose to the heart was 2.5 Gy (0.7 to 9.6 Gy) at FB, 1.2 Gy (0.6 to 3.8 Gy, p < 0.001) at 75% inspiration, 1.1 Gy (0.6 to 3.1 Gy, p = 0.004) at 90% inspiration, 1.0 Gy (0.6 to 3.0 Gy) at 100% inspiration or DIBH, and 1.0 Gy (0.6 to 2.8 Gy, p = 0.019) at 110% inspiration. The average mean dose to the left anterior descending artery (LAD) was 19.9 Gy (2.4 to 46.4 Gy), 8.6 Gy (2.0 to 43.8 Gy, p < 0.001), 7.2 Gy (1.9 to 40.1 Gy, p = 0.035), 6.5 Gy (1.8 to 34.7 Gy), and 5.3 Gy (1.5 to 31.5 Gy, p < 0.001), correspondingly. This novel method enables numerous anatomical situations to be mimicked and quantifies the dosimetric effect they have on a treatment plan.
There are 2 methods commonly used for patient positioning in the anterior-posterior (A-P) direction: one is the skin mark patient setup method (SMPS) and the other is the couch height–based patient setup method (CHPS). This study compared the setup accuracy of these 2 methods for abdominal radiation therapy. The enrollment for this study comprised 23 patients with pancreatic cancer. For treatments (539 sessions), patients were set up by using isocenter skin marks and thereafter treatment couch was shifted so that the distance between the isocenter and the upper side of the treatment couch was equal to that indicated on the computed tomographic (CT) image. Setup deviation in the A-P direction for CHPS was measured by matching the spine of the digitally reconstructed radiograph (DRR) of a lateral beam at simulation with that of the corresponding time-integrated electronic portal image. For SMPS with no correction (SMPS/NC), setup deviation was calculated based on the couch-level difference between SMPS and CHPS. SMPS/NC was corrected using 2 off-line correction protocols: no action level (SMPS/NAL) and extended NAL (SMPS/eNAL) protocols. Margins to compensate for deviations were calculated using the Stroom formula. A-P deviation > 5 mm was observed in 17% of SMPS/NC, 4% of SMPS/NAL, and 4% of SMPS/eNAL sessions but only in one CHPS session. For SMPS/NC, 7 patients (30%) showed deviations at an increasing rate of > 0.1 mm/fraction, but for CHPS, no such trend was observed. The standard deviations (SDs) of systematic error (Σ) were 2.6, 1.4, 0.6, and 0.8 mm and the root mean squares of random error (σ) were 2.1, 2.6, 2.7, and 0.9 mm for SMPS/NC, SMPS/NAL, SMPS/eNAL, and CHPS, respectively. Margins to compensate for the deviations were wide for SMPS/NC (6.7 mm), smaller for SMPS/NAL (4.6 mm) and SMPS/eNAL (3.1 mm), and smallest for CHPS (2.2 mm). Achieving better setup with smaller margins, CHPS appears to be a reproducible method for abdominal patient setup.
Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registering CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.
Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but also on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.
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We report the advancement of materials science at the mesoscale requires improvements in both sampling volumes/areas and spatial resolution in order to make statistically significant measurements of microstructures that influence higher-order material properties, such as fatigue and fracture. Therefore, SEM-based techniques have become desirable due to improvements in imaging resolution, large sample handling capability, and flexibility for in-situ instrumentation. By using fast sampling of SEM electron detector signals, intrinsic beam scanning defects have been identified that are related to the response time of the SEM electron beam deflectors and electron detectors. Mitigation of these beam scanning defects using detector sampling approaches and an adaptive model for settling time is shown to produce higher resolution SEM images, at faster image acquisition times, with a means to quantify the different response functions for various beam deflectors and detectors including those for electrons and ions.
We evaluate the temporal relation between protein expression by cationic lipid-mediated transfection and cell division using time lapse fluorescence microscopy. Detailed image analysis provides new insights on the single cell level while simultaneously achieving appropriate statistics. Earlier evidence by less direct methods such as flow cytometry indicates a primary route for transfection involving nuclear envelope breakdown, but also suggests the existence of a pathway independent of mitosis. We confirm and quantify both mechanisms. We found the timing for successful transfection to be unexpectedly flexible, contrary to assertions of a narrow time window. Specifically, cells dividing more than 24 h after exposure to the transfection medium express the probed protein at a comparable level to cells in a mitotic state during or shortly after transfection. This finding can have a profound impact on the guidance and development of non-viral gene delivery materials. - Highlights: • Cationic lipid-based transfection supports protein expression without cell division. • Protein expression is unrelated to cell cycle status at the time of transfection. • Time-lapse imaging provides direct evaluation without statistical averaging. • Lipoplex dissociation is a likely target for improvement of transfection efficiency.
In this work we tabulate and histogram the image segmentation time for beam’s eye view (BEV) treatment planning in our center. The average time needed to generate contours on CT images delineating normal structures and treatment target volumes is calculated using a data base containing over 500 patients’ BEV plans. The average number of contours and total image segmentation time needed for BEV plans in three common treatment sites, namely, head/neck, lung/chest, and prostate, were estimated.
Images that are collected via scanning transmission electron microscopy (STEM) can be undersampled to avoid damage to the specimen while maintaining resolution [1, 2]. We have used BPFA to impute missing data and reduce noise [3]. The reconstruction is typically evaluated using the peak signal-to-noise ratio (PSNR). This measure is too conservative for STEM images and we propose that the Fourier ring correlation (FRC) is used instead to evaluate the reconstruction. We are not concerned with exact reconstruction of the truth image, and therefore PSNR is a conservative estimation of the quality of the reconstruction. Instead, we are concerned with the visual resolution of the image and whether atoms can be distinguished. We have evaluated the reconstruction of a simulated STEM image using the FRC and compared the results with the PSNR measurements. The FRC captures the resolution of the image and is not affected by a large MSE if the atom peaks are still distinguishable. The noisy and reconstructed images are shown in Figure 1. The simulated STEM image was sampled at 100%, 80%, 40%, and 20% of the original pixels to simulate an undersampled scan. The reconstruction was done using BPFA with a patch size of 10 x 10 and no overlapping patches. Not having overlapping patches produces inferior results but they are still acceptable. The dictionary size is 64 and 30 iterations were completed during each reconstruction. The 100% image was denoised instead of reconstructed. Poisson noise was applied to the simulated image with λ values of 500, 50, and 5 to simulate lower imaging dose. The original simulated STEM image was also included in our calculations and was generated using a dose of 1000. The simulated STEM image is 100 by 100 pixels and has essentially no high frequency components. The image reconstruction tends to smooth the data, also resulting in no high frequency components. This causes the FRC of the two images to be large at higher resolutions and may be misleading. For this reason, the BPFA has no overlap to avoid excessive smoothing. Moreover, the resolution of the simulated image is approximately 9.2 (1/nm), so we only look that far in the frequency domain when performing FRC. If the FRC curve does not crossover the threshold, a resolution value of 9.2 is used. We emphasize that our reported results are conservative. The FRC and PSNR values using the ground truth and the reconstructed images are shown in Tables 1 and 2. The left side show the metrics without using BPFA (missing pixels) and the right side show the metrics after using BPFA. When we did not use BPFA, the Fourier transform was estimated [4]. Some threshold curves have been studied [5], but they are derived for additive noise models. Since we have a Poisson noise model, we have used the more conservative threshold of 0.5 for our calculations. Ten images were used to construct each cell of tables in the form of the mean of the metric plus or minus its standard deviation. As expected, the PSNR dies off much quicker than the FRC values for the same image. For the 100% and 80% sampled versions of the truth image, the resolution only dies off when the dose is 5. However, the PSNR dies off rapidly as the dose is reduced. For the 1000, 500, and 50 dose images, the FRC is the maximum, or close, until we undersample at 20%. The PSNR for these values tapers down as we get into the bottom right hand corner of the table, even though the resolution remains high. Overall, we find that undersampled images can be reconstructed to acceptable resolution even when the dose per pixel is also reduced[6]. References: [1]A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [2]A Stevens, L Kovarik, P Abellan et al. Advanced Structural and Chemical Imaging 1(1), (2015), pp. 1. [3]M Zhou, H Chen, J Paisley et al. Image Processing, IEEE Transactions on 21(1), (2012), pp. 130. [4]V. Y. Liepin’sh. Automatic control and computer sciences 30(3), (1996), pp. 20.
Interferometric scattering microscopy (iSCAT) is a label-free optical microscopy technique that enables imaging of individual nano-objects such as nanoparticles, viruses, and proteins. Essential to this technique is the suppression of background scattering and identification of signals from nano-objects. In the presence of substrates with high roughness, scattering heterogeneities in the background, when coupled with tiny stage movements, cause features in the background to be manifested in background-suppressed iSCAT images. Traditional computer vision algorithms detect these background features as particles, limiting the accuracy of object detection in iSCAT experiments. Here, in this paper, we present a pathway to improve particle detection in such situations using supervised machine learning via a mask region-based convolutional neural network (mask R-CNN). Using a model iSCAT experiment of 19.2 nm gold nanoparticles adsorbing to a rough layer-by-layer polyelectrolyte film, we develop a method to generate labeled datasets using experimental background images and simulated particle signals and train the mask R-CNN using limited computational resources via transfer learning. We then compare the performance of the mask R-CNN trained with and without inclusion of experimental backgrounds in the dataset against that of a traditional computer vision object detection algorithm, Haar-like feature detection, by analyzing data from the model experiment. Results demonstrate that including representative backgrounds in training datasets improved the mask R-CNN in differentiating between background and particle signals and elevated performance by markedly reducing false positives. The methodology for creating a labeled dataset with representative experimental backgrounds and simulated signals facilitates the application of machine learning in iSCAT experiments with strong background scattering and thus provides a useful workflow for future researchers to improve their image processing capabilities.
There are several applications in computational biophysics which require the optimization of discrete interacting states; e.g., amino acid titration states, ligand oxidation states, or discrete rotamer angles. Such optimization can be very time-consuming as it scales exponentially in the number of sites to be optimized. In this paper, we describe a new polynomial-time algorithm for optimization of discrete states in macromolecular systems. This algorithm was adapted from image processing and uses techniques from discrete mathematics and graph theory to restate the optimization problem in terms of maximum flow-minimum cut graph analysis. The interaction energy graph, a graph in which vertices (amino acids) and edges (interactions) are weighted with their respective energies, is transformed into a flow network in which the value of the minimum cut in the network equals the minimum free energy of the protein, and the cut itself encodes the state that achieves the minimum free energy. Because of its deterministic nature and polynomial-time performance, this algorithm has the potential to allow for the ionization state of larger proteins to be discovered.