The role of machine and deep learning in modern medical physics

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155454/1/mp14088_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155454/2/mp14088.pd

Network Centralities in Quantum Entanglement Distribution due to User Preferences

Quantum networks are of great interest of late which apply quantum mechanics to transfer information securely. One of the key properties which are exploited is entanglement to transfer information from one network node to another. Applications like quantum teleportation rely on the entanglement between the concerned nodes. Thus, efficient entanglement distribution among network nodes is of utmost importance. Several entanglement distribution methods have been proposed in the literature which primarily rely on attributes, such as, fidelities, link layer network topologies, proactive distribution, etc. This paper studies the centralities of the network when the link layer topology of entanglements (referred to as entangled graph) is driven by usage patterns of peer-to-peer connections between remote nodes (referred to as connection graph) with different characteristics. Three different distributions (uniform, gaussian, and power law) are considered for the connection graph where the two nodes are selected from the same distribution. For the entangled graph, both reactive and proactive entanglements are employed to form a random graph. Results show that the edge centralities (measured as usage frequencies of individual edges during entanglement distribution) of the entangled graph follow power law distributions whereas the growth in entanglements with connections and node centralities (degrees of nodes) are monomolecularly distributed for most of the scenarios. These findings will help in quantum resource management, e.g., quantum technology with high reliability and lower decoherence time may be allocated to edges with high centralities

Assessment of PlanIQ Feasibility DVH for head and neck treatment planning

INTRODUCTION: Designing a radiation plan that optimally delivers both target coverage and normal tissue sparing is challenging. There are limited tools to determine what is dosimetrically achievable and frequently the experience of the planner/physician is relied upon to make these determinations. PlanIQ software provides a tool that uses target and organ at risk (OAR) geometry to indicate the difficulty of achieving different points for organ dose-volume histograms (DVH). We hypothesized that PlanIQ Feasibility DVH may aid planners in reducing dose to OARs. METHODS AND MATERIALS: Clinically delivered head and neck treatments (clinical plan) were re-planned (re-plan) putting high emphasis on maximally sparing the contralateral parotid gland, contralateral submandibular gland, and larynx while maintaining routine clinical dosimetric objectives. The planner was blinded to the results of the clinically delivered plan as well as the Feasibility DVHs from PlanIQ. The re-plan treatments were designed using 3-arc VMAT in Raystation (RaySearch Laboratories, Sweden). The planner was then given the results from the PlanIQ Feasibility DVH analysis and developed an additional plan incorporating this information using 4-arc VMAT (IQ plan). The DVHs across the three treatment plans were compared with what was deemed "impossible" by PlanIQ's Feasibility DVH (Impossible DVH). The impossible DVH (red) is defined as the DVH generated using the minimal dose that any voxel outside the targets must receive given 100% target coverage. RESULTS: The re-plans performed blinded to PlanIQ Feasibilty DVH achieved superior sparing of aforementioned OARs compared to the clinically delivered plans and resulted in discrepancies from the impossible DVHs by an average of 200-700 cGy. Using the PlanIQ Feasibility DVH led to additionalOAR sparing compared to both the re-plans and clinical plans and reduced the discrepancies from the impossible DVHs to an average of approximately 100 cGy. The dose reduction from clinical to re-plan and re-plan to IQ plan were significantly different even when taking into account multiple hypothesis testing for both the contralateral parotid and the larynx (P < 0.004 for all comparisons). No significant differences were observed between the three plans for the contralateral parotid when considering multiple hypothesis testing. CONCLUSIONS: Clinical treatment plans and blinded re-plans were found to suboptimally spare OARs. PlanIQ could aid planners in generating treatment plans that push the limits of OAR sparing while maintaining routine clinical target coverage goals

Noninvasive measurement of tissue blood oxygenation with Cerenkov imaging during therapeutic radiation delivery

Tumor tissue oxygenation significantly affects the outcome of radiotherapy. Real-time monitoring of tumor hypoxia is highly desirable for effective radiotherapy, and is the basis for improved treatment because hypoxic tumor cells are more resistant to radiation damage than fully oxygenated cells. We propose to use Cerenkov imaging to monitor tumor hypoxia by means of tissue blood oxygenation without the need for any exogenous contrast agent. Using a rodent hypoxia model, we demonstrate that Cerenkov imaging can be used as a noninvasive and noncontact method to measure tissue blood oxygenation level during radiation delivery. The data from Cerenkov imaging were validated using near infrared spectrometry methods. The results demonstrate the feasibility of using Cerenkov imaging to monitor tumor hypoxia during therapeutic radiation delivery

Effect of super-optimal levels of fertilizers on soil enzymatic activities during growth stages of wheat crop on an Inceptisol

A field experiment was conducted during 2010-2011 and 2011-2012 to investigate the effect of optimal (100% NPK) to super-optimal doses (200% NPK) of mineral fertilizers on soil enzymes such as dehydrogenase (DHA), acid phosphatase (Ac-PA), alkaline phosphatase (Alk-PA), fluorescien diacetate hydrolysis (FDA), urease and nitrate reductase (NRA) at three physiological stages (CRI, anthesis and maturity) of wheat crop on an Inceptisol. Dehydrogenase activity was reduced by 28-37% when fertilizer application was at super-optimal dose (200% NPK), whereas, urease and NRA responded positively in the range of 43-44% and 213-231% respectively. Alk-PAwas 7.3-7.9% higher in treatments receiving 125% NPK as compared to control (100% NPK); whereas, Ac-PA declines in the plots receiving 175 and 200% of recommended dose of fertilizer (RDF) as compared to 150% NPK levels. Addition of 175% RDF increased the FDA to the tune of 46-53% as compared to 100% NPK. A significant (P?0.05) positive interaction between fertilizer treatments and physiological stages of wheat growth was observed on soil enzyme activities (except urease and NRA) being highest at the anthesis stage of wheat. Correlation matrix analysis showed that DHA was correlated with the studied enzyme activities except Ac-PA and FDA; whereas, strong correlation was observed between urease and NRA (r=0.981, P=0.01). This study provides theoretical and practical base for avoiding super optimal application of fertilisers which hinders the enzyme activities and vis-a-vis sustainable nutrient enrichment under rhizosphere

Numerical Analysis on MHD mixed convection flow of Al_2O_3/H_2O (Aluminum-Water) Nanofluids in a Vertical Square Duct

In this work, we have considered steady laminar magnetohydrodynamics (MHD) mixed convection flow of an electrically conducting fluid in presence of nanoparticles while water as the base fluid in a vertical square duct. The walls of the duct are thermally insulated. In the energy equation, the effect of viscous dissipation and Joule heat is also considered. In this case, the walls of the duct are kept at a constant temperature. By using dimensionless quantities the governing equations of momentum, induction, and energy are first transformed into dimensionless equations. The velocity, temperature, and induced magnetic field profiles are plotted to analyze the effect of different flow parameters. It is found that the nanofluid motion expedite with the increase of the value of the parameters magnetic Reynolds number and Prandtl number. There are some important industrial applications and cooling shows in the industry of the current research. This study observed its importance with the view to increasing the heat transfer efficiency practical application relevant to industry and engineering issues. The issues discussed in this study have not been included in the earlier investigation for steady nanofluid flow due to a square duct. Numerical results are matched with an earlier published work and an excellent agreement between two are observed.

Machine Learning to Generate Adjustable Dose Distributions in Head-and-Neck Cancer Radiation Therapy

In this work, we propose a Machine Learning model that generates an adjustable 3D dose distribution for external beam radiation therapy for head-and-neck cancer treatments. In contrast to existing Machine Learning methods that provide a single model, we create pairs of models for each organ-at-risk, namely lower-extreme and upper-extreme models. These model pairs for an organ-at-risk propose doses that give lower and higher doses to that organ-at-risk, while also encapsulating the dose trade-off to other organs-at-risk. By weighting and combining the model pairs for all organs-at-risk, we are able to dynamically create adjustable dose distributions that can be used, in real-time, to move doses between organs-at-risk, thereby customizing the dose distribution to the needs of a particular patient. We leverage a key observation that the training data set inherently contains the clinical trade-offs. We show that the adjustable distributions are able to provide reasonable clinical dose latitude in the trade-off of doses between organs-at-risk

MIXED MODE PERFORMANCE OF GAAS UTB-MOSFET WITH EXTRA INSULATOR REGION AND UNDOPED BURIED OXIDE REGION

Investigation of mixed mode performances for GaAs UTB-MOSFET at nanoscale regime keeping in view of “Beyond CMOS” is the current trend of semiconductor industry. Here it is proposed to modify conventional models by considering an extra Insulator Region (IR) and Undoped Buried oxide Region (UBR) to study the performance related to digital and analog/RF applications. Here a GaAs is considered as the channel material. The IR-UTB-SOI-n-MOSFET has shown promising results with respect to SS, DIBL, fT and switching speed