Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases

The purpose of this work was to study and quantify the differences in dose distributions computed with some of the newest dose calculation algorithms available in commercial planning systems. The study was done for clinical cases originally calculated with pencil beam convolution (PBC) where large density inhomogeneities were present. Three other dose algorithms were used: a pencil beam like algorithm, the anisotropic analytic algorithm (AAA), a convolution superposition algorithm, collapsed cone convolution (CCC), and a Monte Carlo program, voxel Monte Carlo (VMC++). The dose calculation algorithms were compared under static field irradiations at 6 MV and 15 MV using multileaf collimators and hard wedges where necessary. Five clinical cases were studied: three lung and two breast cases. We found that, in terms of accuracy, the CCC algorithm performed better overall than AAA compared to VMC++, but AAA remains an attractive option for routine use in the clinic due to its short computation times. Dose differences between the different algorithms and VMC++ for the median value of the planning target volume (PTV) were typically 0.4% (range: 0.0 to 1.4%) in the lung and -1.3% (range: -2.1 to -0.6%) in the breast for the few cases we analysed. As expected, PTV coverage and dose homogeneity turned out to be more critical in the lung than in the breast cases with respect to the accuracy of the dose calculation. This was observed in the dose volume histograms obtained from the Monte Carlo simulations.

The accuracy of FAST in relation to grade of solid organ injuries: a retrospective analysis of 226 trauma patients with liver or splenic lesion

BACKGROUND: This study investigated the role of a negative FAST in the diagnostic and therapeutic algorithm of multiply injured patients with liver or splenic lesions. METHODS: A retrospective analysis of 226 multiply injured patients with liver or splenic lesions treated at Bern University Hospital, Switzerland. RESULTS: FAST failed to detect free fluid or organ lesions in 45 of 226 patients with spleen or liver injuries (sensitivity 80.1%). Overall specificity was 99.5%. The positive and negative predictive values were 99.4% and 83.3%. The overall likelihood ratios for a positive and negative FAST were 160.2 and 0.2. Grade III-V organ lesions were detected more frequently than grade I and II lesions. Without the additional diagnostic accuracy of a CT scan, the mean ISS of the FAST-false-negative patients would be significantly underestimated and 7 previously unsuspected intra-abdominal injuries would have been missed. CONCLUSION: FAST is an expedient tool for the primary assessment of polytraumatized patients to rule out high grade intra-abdominal injuries. However, the low overall diagnostic sensitivity of FAST may lead to underestimated injury patterns and delayed complications may occur. Hence, in hemodynamically stable patients with abdominal trauma, an early CT scan should be considered and one must be aware of the potential shortcomings of a "negative FAST".

Food Volume Computation for Self Dietary Assessment Applications

There is great demand for easily-accessible, user-friendly dietary self-management applications. Yet accurate, fully-automatic estimation of nutritional intake using computer vision methods remains an open research problem. One key element of this problem is the volume estimation, which can be computed from 3D models obtained using multi-view geometry. The paper presents a computational system for volume estimation based on the processing of two meal images. A 3D model of the served meal is reconstructed using the acquired images and the volume is computed from the shape. The algorithm was tested on food models (dummy foods) with known volume and on real served food. Volume accuracy was in the order of 90 %, while the total execution time was below 15 seconds per image pair. The proposed system combines simple and computational affordable methods for 3D reconstruction, remained stable throughout the experiments, operates in near real time, and places minimum constraints on users.

Excitation and charge transfer in H-H+ collisions at 5-80 keV and application to astrophysical shocks

In astrophysical regimes where the collisional excitation of hydrogen atoms is relevant, the cross-sections for the interactions of hydrogen atoms with electrons and protons are necessary for calculating line profiles and intensities. In particular, at relative velocities exceeding ∼1000 km s−1, collisional excitation by protons dominates over that by electrons. Surprisingly, the H–H+ cross-sections at these velocities do not exist for atomic levels of n≥ 4, forcing researchers to utilize extrapolation via inaccurate scaling laws. In this study, we present a faster and improved algorithm for computing cross-sections for the H–H+ collisional system, including excitation and charge transfer to the n≥ 2 levels of the hydrogen atom. We develop a code named BDSCX which directly solves the Schrödinger equation with variable (but non-adaptive) resolution and utilizes a hybrid spatial-Fourier grid. Our novel hybrid grid reduces the number of grid points needed from ∼4000n6 (for a ‘brute force’, Cartesian grid) to ∼2000n4 and speeds up the computation by a factor of ∼50 for calculations going up to n= 4. We present (l, m)-resolved results for charge transfer and excitation final states for n= 2–4 and for projectile energies of 5–80 keV, as well as fitting functions for the cross-sections. The ability to accurately compute H–H+ cross-sections to n= 4 allows us to calculate the Balmer decrement, the ratio of Hα to Hβ line intensities. We find that the Balmer decrement starts to increase beyond its largely constant value of 2–3 below 10 keV, reaching values of 4–5 at 5 keV, thus complicating its use as a diagnostic of dust extinction when fast (∼1000 km s−1) shocks are impinging upon the ambient interstellar medium.

Systematic analysis of the intravoxel incoherent motion threshold separating perfusion and diffusion effects: Proposal of a standardized algorithm

PURPOSE To systematically evaluate the dependence of intravoxel-incoherent-motion (IVIM) parameters on the b-value threshold separating the perfusion and diffusion compartment, and to implement and test an algorithm for the standardized computation of this threshold. METHODS Diffusion weighted images of the upper abdomen were acquired at 3 Tesla in eleven healthy male volunteers with 10 different b-values and in two healthy male volunteers with 16 different b-values. Region-of-interest IVIM analysis was applied to the abdominal organs and skeletal muscle with a systematic increase of the b-value threshold for computing pseudodiffusion D*, perfusion fraction Fp , diffusion coefficient D, and the sum of squared residuals to the bi-exponential IVIM-fit. RESULTS IVIM parameters strongly depended on the choice of the b-value threshold. The proposed algorithm successfully provided optimal b-value thresholds with the smallest residuals for all evaluated organs [s/mm2]: e.g., right liver lobe 20, spleen 20, right renal cortex 150, skeletal muscle 150. Mean D* [10(-3) mm(2) /s], Fp [%], and D [10(-3) mm(2) /s] values (±standard deviation) were: right liver lobe, 88.7 ± 42.5, 22.6 ± 7.4, 0.73 ± 0.12; right renal cortex: 11.5 ± 1.8, 18.3 ± 2.9, 1.68 ± 0.05; spleen: 41.9 ± 57.9, 8.2 ± 3.4, 0.69 ± 0.07; skeletal muscle: 21.7 ± 19.0; 7.4 ± 3.0; 1.36 ± 0.04. CONCLUSION IVIM parameters strongly depend upon the choice of the b-value threshold used for computation. The proposed algorithm may be used as a robust approach for IVIM analysis without organ-specific adaptation. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

A Genetic Algorithm to associate optical measurements and estimate orbits of geocentric objects

Cataloging geocentric objects can be put in the framework of Multiple Target Tracking (MTT). Current work tends to focus on the S = 2 MTT problem because of its favorable computational complexity of O(n²). The MTT problem becomes NP-hard for a dimension of S˃3. The challenge is to find an approximation to the solution within a reasonable computation time. To effciently approximate this solution a Genetic Algorithm is used. The algorithm is applied to a simulated test case. These results represent the first steps towards a method that can treat the S˃3 problem effciently and with minimal manual intervention.

A study of the time complexity of an Elitist Genetic Algorithm used for associating optical observations of MEO and GEO Space Debris

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.