Reduce Background Noise Research Articles

Ti3C2/Cu2O heterostructure based signal-off photoelectrochemical sensor for high sensitivity detection of glucose

Photoelectrochemical (PEC) sensing has emerged as a simple and practical method for the analysis and detection, its separated optical signal and detection electrical signal give it the advantages of reduced background noise and outstanding sensitivity. Here, we synthesized a Ti3C2/Cu2O composite through simple oil bath heating process, whose excellent PEC performance and sensitive photoelectric response to glucose make it a propitious substitution to glucose oxidase. On this basis, we construct a PEC non-enzymatic sensor based on the Ti3C2/Cu2O heterostructure for the detection of glucose. Under the optimal conditions, the photocurrent of Ti3C2/Cu2O is linear with the logarithm value of glucose concentration in the wide range of 0.5 nM to 0.5 mM with a detection limit of 0.17 nM. Furthermore, the successful detection of glucose in standard samples and human serum by the proposed Ti3C2/Cu2O based PEC non-enzymatic sensor demonstrates the application prospect of heterostructure material in PEC sensor, which provides a new thought for the design and construction of PEC non-enzymatic sensing platform.

Advances in exploration geochemistry, 2007 to 2017 and beyond

Mineral exploration under relatively young, exotic cover still presents a major challenge to discovery. Advances and future developments can be categorized in four key areas, (1) understanding metal mobility and mechanisms, (2) rapid geochemical analyses, (3) data access, integration and interoperability and (4) innovation in laboratory-based methods. Application of ‘regolith-style' surface mapping in covered terrains outside of conventional lateritic terrains is achieving success in terms of reducing background noise and improving geochemical contrasts. However, process models for anomaly generation are still uncertain and require further research. The interaction between the surface environment, microbes, hydrocarbons and chemistry is receiving greater attention. While significant progress has been achieved in understanding the role of vegetation, interaction with the water table and cycling of metals in the near surface environment in Australia, other regions of the world, for example, the till-covered terrains in the northern hemisphere and arid colluvium-covered areas of South America, have seen less progress. In addition to vegetation, the influence of bacteria, fungi and invertebrates is not as well studied with respect to metal mobilization in cover. Field portable XRF has become a standard field technique, though more often used in a camp setting. Apart from a tweaking of analytical quality, instruments have probably reached their peak of analytical development with add-ons, such as cameras, beam-limiters, wireless transmission and GPS as the main differences between instrument suppliers. Their future rests in automated application in unconventional configurations, for example, core scanning and better integration of analytical data with other information such as spectral analyses. Pattern drilling that persists in industry, however, has benefited from innovative application of field-portable tools along with rock and mineral chemistry to provide near real-time results and assist in a shift toward more flexible and targeted drilling in greenfields settings. Innovation in the laboratory continues to progress. More selective geochemical analysis, imaging of fine particle size fractions and resistate mineral phases and isotope analysis are faster and more accessible than ever before. The application of genomics (and data analysis) as mineral exploration tools is on the horizon. A continuing problem in geoscience, the supply to industry of suitably trained geochemists, persists although some needs, particularly at junior level, will be met by recent initiatives at various universities at graduate level. Unfortunately, the current economic climate has had a significant impact on R&D and retention of geochemistry skills by the industry. Whilst the future is positive, significant investment is required to develop the next generation of geochemical exploration tools and concepts. Thematic collection: This article is part of the Exploration 17 collection available at: https://www.lyellcollection.org/cc/exploration-17

Ultrahigh-resolution spectrometer based on 19 integrated gratings

Optical spectrometers play a key role in acquiring rich photonic information in both scientific research and a wide variety of applications. In this work, we present a new spectrometer with an ultrahigh resolution of better than 0.012 nm/pixel in the 170–600 nm spectral region using a grating-integrated module that consists of 19 subgratings without any moving parts. By using two-dimensional (2D) backsideilluminated complementary metal-oxide-semiconductor (BSI-CMOS) array detector technology with 2048 × 2048 pixels, a high data acquisition speed of approximately 25 spectra per second is achieved. The physical photon-sensing size of the detector along the one-dimensional wavelength direction is enhanced by a factor of 19 to approximately 428 mm, or 38912 pixels, to satisfy the requirement of seamless connection between two neighboring subspectral regions without any missing wavelengths throughout the entire spectral region. As tested with a mercury lamp, the system has advanced performance capabilities characterized by the highest k parameter reported to date, being approximately 3.58 × 104, where k = (working wavelength region)/(pixel resolution). Data calibration and analysis as well as a method of reducing background noise more efficiently are also discussed. The results presented in this work will stimulate further research on precision spectrometers based on advanced BSI-CMOS array detectors in the future.

Abstract 413: Development of a Highly Customizable Platform for Variant Detection in Circulating Tumor DNA

Abstract Introduction: Variant detection in circulating tumor DNA (ctDNA) provides an unprecedented opportunity to study the mutational landscape of cancers with minimal patient invasiveness. Meanwhile, new variants providing information about drug response and disease prognosis are being rapidly discovered. Therefore, to fully harness the power of ctDNA variant detection it is critical to be able to rapidly modify the set of variants targeted in an assay. Here we present a platform for next generation sequencing-based ctDNA assays that allows researchers to readily customize their panel targets. Methods: Anchored Multiplex PCR (AMP™) is a molecular biology technique that allows for near infinite modularity of assay targets while maintaining variant detection sensitivity. In order to ensure assay specificity, AMP utilizes molecular barcoded adapters (MBC) to uniquely label input molecules prior to amplification, enabling post-sequencing error correction. This increases analytical sensitivity by reducing background noise. We also developed bioinformatics methods, which allow the characterization of position-specific error levels. By combining molecular barcode-based error correction and error profile characterization, we can reliably detect low frequency variants with high specificity. Results: We tested the modularity of the AMP ctDNA platform by creating ctDNA panels targeting either 6 kb of cancer variant hotspots or 34 kb of tumor suppressors plus the same 6kb of cancer hotspots (40 kb total target sequence). We then prepared and sequenced libraries using ctDNA-like inputs containing important cancer variants at low allele fractions (AF). We used these data to characterize the noise inherent in AMP library preparation and Illumina sequencing. We then performed a power analysis to measure the lowest AF at which we could detect variants at each target position given the noise level and sequencing coverage. Our results show that we can confidently detect variants with an AF of less than 0.18% in 50% of bases and 0.47% in 95% of bases covered in the 6kb panel. Variant detection sensitivity remained consistent over the 6kb of hotspot targets in the context of the 40kb panel (50% of bases powered to detect 0.17% AF variants and 95% powered to detect 0.45% variants). Across the full 40kb of the larger panel we had statistical power to call 0.23% AF variants at 50% of target bases and to call 0.56% variants at 95% of target bases. These data demonstrate that ctDNA panels can maintain assay performance upon panel modifications. Conclusions: The modular nature of AMP ctDNA panels allows for endless combinations of targeted genes to maximize detection sensitivity in relevant regions while also maintaining assay performance. Our experience with AMP assays indicates that the range in the number of targets that can be included in a panel is quite large, allowing broad implementation of the assays developed on the AMP platform. Citation Format: Matt Egleston, Paula Roberts, Ian Hoskins, Aaron Garnett, Laura Griffin, Abel Licon, Ryan Walters. Development of a Highly Customizable Platform for Variant Detection in Circulating Tumor DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 413.

Deep neural networks for single shot structured light profilometry.

In 3D optical metrology, single-shot structured light profilometry techniques have inherent advantages over their multi-shot counterparts in terms of measurement speed, optical setup simplicity, and robustness to motion artifacts. In this paper, we present a new approach to extract height information from single deformed fringe patterns, based entirely on deep learning. By training a fully convolutional neural network on a large set of simulated height maps with corresponding deformed fringe patterns, we demonstrate the ability of the network to obtain full-field height information from previously unseen fringe patterns with high accuracy. As an added benefit, intermediate data processing steps such as background masking, noise reduction and phase unwrapping that are otherwise required in classic demodulation strategies, can be learned directly by the network as part of its mapping function.

Direct Analysis of Carbonyl Compounds by Mass Spectrometry with Double-Region Atmospheric Pressure Chemical Ionization.

Direct analysis of highly reactive volatile species such as the aliphatic aldehydes as vital biomarkers remains a great challenge due to difficulties in the sample pretreatment. To address such a challenge, we herein report the development of a novel double-region atmospheric pressure chemical ionization mass spectrometry (DRAPCI-MS) method. The DRAPCI source implements a separated structural design that uses a focus electrode to divide the discharge and ionization region to reduce sample fragmentation in the ionization process. Counterflow introduction (CFI) configuration was adopted in the DRAPCI source to reduce background noise, while ion transmission efficiency was optimized through simulating the voltage of the focus electrode and the ion trajectory of the ion source. The limits of detection (LODs) of four carbonyl compounds cyclohexanone, hexanal, heptanal, and octanal by DRAPCI-MS were between 0.1 and 3 μg·m-3, approximately two to eight times lower than those by atmospheric pressure chemical ionization mass spectrometry. Additionally, the DRAPCI-MS method carried out effective in situ analyses of the volatile components in expired milk and the exhaled breath of smokers, demonstrating the DRAPCI-MS as a practical tool to analyze complex mixtures. The DRAPCI-MS method provides a rapid, sensitive, and high-throughput technique in the real-time analysis of gaseous small-molecule compounds.

Ultrashort-pulse laser-induced breakdown spectroscopy for detecting airborne metals during energetic reactions.

Ultrashort-pulse laser-induced breakdown spectroscopy (LIBS), specifically using a femtosecond laser, has certain advantages over longer-pulse, nanosecond-duration lasers, in that they typically have kilohertz repetition rates and reduced background noise along with little-to-no laser-plasma interaction, all of which lead to a better chance of detecting LIBS signals from trace particles. In this work, femtosecond-LIBS is investigated for the detection of metallic particles in the hot flame zone of solid propellant strands burning in the atmosphere. The metallic particles doped into the solid propellants were aluminum (Al), copper, lead, lead stearate, and mercury chloride, which are all either typically found in energetic formulations as additives or impurities. Using an 80-fs-pulse-duration, amplified Ti:Sapphire laser operating at 1000 Hz, single-shot concentration measurement experiments were performed. The femtosecond-LIBS apparatus could detect all metallic additives, whereas a previous nanosecond-LIBS scheme with comparable conditions was able to detect only higher concentrations of Al. The single-shot concentration study, conducted with the Al-doped propellants, indicated that there is a linear relationship between the percentage of laser shots detecting a LIBS signal and the mass percentage of Al initially present in the strands. The present results illustrate the advantages of using a femtosecond laser over a nanosecond laser for LIBS detection during energetics material reactions.

Resolution-enhanced imaging through scattering media by high-order correlation.

Super-resolution optical imaging is a rapidly emerging technology enabling many applications. Recently, correlation imaging has shown its capability in imaging beyond the diffraction limit, relying on quantum and statistical properties of light. High-order correlation imaging can further enhance resolution, however, at the expense of complicated algorithms. Here, we experimentally demonstrate a resolution-enhanced method of imaging through scattering media by exploiting high-order correlation of fluorescence light. Based on this method, individual fluorophores' temporal fluctuations are recorded and computed for their distinguished high-order correlations that enable super-resolution. Special designed time sequences are chosen to reduce computation time and memory. Such high-order correlation imaging exhibits reliable performance through scattering media with significant resolution enhancement and background noise reduction. This efficient imaging method paves the way for new biomedical applications.

Smart Wristwatches Employing Finger-Conducted Voice Transmission System

The principal aim of this paper is to present a novel speech transmission system that conveys speech between an actuator in a wearable wristwatch and the ear bone of a user through a finger. If an individual wears a smart watch equipped with an actuator that can play speech sent via communication lines, speech vibrations propagate from the actuator to fingertips through the human tissue and bone. When an individual places his or her finger into their ear, speech conducted through the finger can be registered and heard. While listening to finger-conducted speech, sounds are muffled, significantly degrading the intelligibility of speech. To mitigate this problem, a formant enhancement filter is applied to the speech prior to being fed into the actuator. With this method, the impulse response of human tissue and bones between the fingertips and wrist on which the watch is worn is first estimated to account for speaker-dependent distortion. Based on the estimated impulse response, a gain filter is used to boost the sound spectra, especially within the formant regions, to compensate for frequency distortion prior to speech transmission. On the other hand, since the impulse responses of humans are quite different for each individual, we propose the novel idea of a personalized algorithm that guides users to select an appropriate gain filter, using the k-medoids clustering algorithm. Also, when an individual uses the proposed system, speech quality is degraded due to the ambient noise and acoustic echo between the microphone and actuator in the watch. Thus, to reduce background noise and acoustic echo, an integrated acoustic echo and background noise suppression algorithm is employed. Extensive simulations of the proposed system were performed by creating a novel phantom, which mimics the human hand with an aid of an ear simulator. We demonstrate that the proposed system has improved speech quality, when transmitting speech from the wearable wristwatch to a human perceptual organ through the finger.

High-Resolution Power Spectral Estimation Method Using Deconvolution

Spectral analysis is a significant technique applied in many fields to infer the signal spectral contents. However, the frequency resolution of a signal spectrum estimation result is limited by its finite data length, especially when using a Fourier-based method. Extra processing gain [i.e., signal-to-noise ratio (SNR) improvement] is always required for weak target detection. In this paper, a high-resolution spectrum estimation method using a deconvolution algorithm is proposed. According to classical spectral analysis, a power spectrum derived from a finite data length is related to the convolution of the true power spectrum from an infinite length data set with the power spectrum from a window function. Therefore, using a deconvolution algorithm on the power spectrum estimated by classical spectral analysis can remove the influence from the window function, such as spectral leakage. The deconvolved power spectrum can robustly obtain a sufficiently high-frequency resolution and low sidelobes with relatively few calculations. The proposed method can also provide a deconvolution gain, which plays an important role in weak signal detection as it is capable of enhancing the signal and reducing background noise. Its performance is analyzed in simulations as well as with measured experimental data.

基于涡旋滤波的图像边缘增强研究进展

As an important means of image processing, the edge enhancement techniques play an important role in amplitude-contrast and phase-contrast objects imaging. The vortex filtering techniques based on radial Hilbert transform have attracted much attention because it can achieve isotropic edge enhancement. However, the classical vortex filtering causes background noise and contrast reduction due to diffraction caused by central singularities and sharp edges. In recent years, many research groups have proposed new types of vortex filters for vortex filtering side lobe suppression. In addition, the isotropic and anisotropic edge enhancement techniques based on vortex filtering have also developed rapidly. In this paper, several methods for suppressing vortex side lobes were summarized in recent years, including Laguerre Gaussian amplitude modulation, Bessel-like amplitude modulation, and Airy amplitude modulation. What's more, from two aspects:scalar vortex filtering and vector vortex filtering, the isotropic and anisotropic edge enhancement methods and progress were reviewed.

Photo-acoustic technology applied to ppb level NO<sub>2</sub> detection by using low power blue diode laser

Photo-acoustic technology based on a low power blue diode laser for measuring the ppb level NO<sub>2</sub> is presented in this paper. A low-cost NO<sub>2</sub> measurement system based on traditional photo-acoustic technology is established. The 405 nm blue diode laser with an external modulation is used as a light source. The central wavelength of the laser is 403.56 nm, the half-peak full width is 0.84 nm, and the power is 65.3 mW. The effective absorption cross section of NO<sub>2</sub> is obtained, and the interference of the water vapor and other trace gasisinvestigated. The resonant frequency is tested to be 1.35 kHz by frequency scanning fitting. An internally polished and coated poly tetra fluoroethylene aluminum cylindrical cavity is used as a photo-acoustic resonator (the inner diameter is 8 mm and the length is 120 mm). The influence factors caused by cavity parameters, optical windows and power supply are studied. The system is optimized to reduce background noise and improve signal-to-noise ratio. Then the noise signal is dropped to 0.02 <inline-formula><tex-math id="M4">\begin{document}${\text{μV}}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20182262_M4.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20182262_M4.png"/></alternatives></inline-formula>. An additional buffer chamber is integrated on the original buffer chamber to form a two-level buffer. The two-stage buffer structure significantly suppresses the effects of airflow noise and improves the system stability. The slope of the calibration curve of the system after linear fitting is 0.016 <inline-formula><tex-math id="M5">\begin{document}${\text{μV/ppb}}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20182262_M5.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20182262_M5.png"/></alternatives></inline-formula>, and R<sup>2</sup> is 0.998. The NO<sub>2</sub> detection limit of system is 2 ppb (3<inline-formula><tex-math id="M6">\begin{document}$\sigma$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20182262_M6.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20182262_M6.png"/></alternatives></inline-formula>) with an average time of 60 s. To verify the results of the system, a diode laser cavity ring-down spectroscopy system (CRDS system, using a 409 nm the diode laser, with a system detection limit of 6.6 × 10<sup>–1</sup>) is used to measure ambient NO<sub>2</sub> simultaneouslyon Lake Dong-Pu in western Hefei, Anhui Province, China. During the experiment, the measured NO<sub>2</sub> concentration ranges from 8 to 30 ppb, with an average concentration of 20.8 ppb. The results of two systems have good consistency:alinear fitting slope of 0.94 ± 0.009, an intercept of 1.89 ± 0.18 and acorrelation coefficient of 0.87. The experimental results show that the system can realize the low-cost on-line detection of the ppb level NO<sub>2</sub>, and it can also be used for the real-time detection of NO<sub>2</sub> concentration field.

Interstellar communication: The colors of optical SETI

It has recently been argued from a laser engineering point of view that there are only a few magic colors for optical SETI. These are primarily the Nd:YAG line at 1064 nm and its second harmonic 532.1 nm. Next best choices would be the sum frequency and/or second harmonic generation of Nd:YAG and Nd:YLF laser lines, 393.8 nm (near Fraunhofer CaK), 656.5 nm (H$\alpha$) and 589.1 nm (NaD2). In this paper, we examine the interstellar extinction, atmospheric transparency and scintillation, as well as noise conditions for these laser lines. For strong signals, we find that optical wavelengths are optimal for distances $d\lesssim\,$kpc. Nd:YAG at $\lambda=1{,}064\,$nm is a similarly good choice, within a factor of two, under most conditions and out to $d\lesssim3\,$kpc. For weaker transmitters, where the signal-to-noise ratio with respect to the blended host star is relevant, the optimal wavelength depends on the background source, such as the stellar type. Fraunhofer spectral lines, while providing lower stellar background noise, are irrelevant in most use cases, as they are overpowered by other factors. Laser-pushed spaceflight concepts, such as "Breakthrough Starshot", would produce brighter and tighter beams than ever assumed for OSETI. Such beamers would appear as naked eye stars out to kpc distances. If laser physics has already matured and converged on the most efficient technology, the laser line of choice for a given scenario (e.g., Nd:YAG for strong signals) can be observed with a narrow filter to dramatically reduce background noise, allowing for large field-of-view observations in fast surveys.

Ordered subset expectation maximization algorithm for positron emission tomographic image reconstruction using belief kernels.

The aim of this study is to investigate the benefits of incorporating prior information in list mode, time-of-flight (TOF) positron emission tomography (PET) image reconstruction using the ordered subset expectation maximization (OSEM) algorithm. This investigation consists of an IEC phantom study and a patient study. For the image under reconstruction, the activity profile along a line of response is treated as a priori and is combined with the TOF measurement to define a belief kernel used for forward and backward projections during the OSEM image reconstruction. Activity profiles are smoothed and combined with the TOF kernels to control the adverse impact of noise, and different levels of smoothness are attempted. The standard TOF OSEM reconstruction is used as a baseline for comparison. Image quality is assessed using a combination of visual assessment and quantitative measurement including contrast recovery coefficients (CRC) and background variability. On the IEC phantom study, the reconstruction using belief kernels converges faster and the reconstructed images are more appealing. The CRCs for all sizes of regions of interest on images reconstructed with belief kernels are higher than those of the baseline. The background variability, measured as a coefficient of variation, is generally lower for the images reconstructed using belief kernels. Similar observations occur on the patient study. Particularly, the images reconstructed using belief kernels have better defined lesions, improved contrast, and reduced background noise. OSEM PET image reconstruction using belief kernels that combine the information from prior images and TOF measurements seems promising and worth further investigation.

Quantum interference and correlation control of frequency-bin qubits

Quantum information is the next frontier in information science, promising unconditionally secure communications, enhanced channel capacities, and computing capabilities far beyond their classical counterparts. And as quantum information processing devices continue to transition from the lab to the field, the demand for the foundational infrastructure connecting them with each other and their users---the quantum internet---will only increase. Due to the remarkable success of frequency multiplexing and control in the classical internet, quantum information encoding in optical frequency offers an intriguing synergy with state-of-the-art fiber-optic networks. Yet coherent quantum frequency operations prove extremely challenging, due to the difficulties in mixing frequencies efficiently, arbitrarily, in parallel, and with low noise. Here we implement an original approach based on a reconfigurable quantum frequency processor, designed to perform arbitrary manipulations of spectrally encoded qubits. This processor's unique tunability allows us to demonstrate frequency-bin Hong-Ou-Mandel interference with record-high 94% visibility. Furthermore, by incorporating such tunability with our method's natural parallelizability, we synthesize independent quantum frequency gates in the same device, realizing the first high-fidelity flip of spectral correlations on two entangled photons. Compared to quantum frequency mixing approaches based on nonlinear optics, our linear method removes the need for additional pump fields and significantly reduces background noise. Our results demonstrate multiple functionalities in parallel in a single platform, representing a huge step forward for the frequency-multiplexed quantum internet.

Automatic Arrival Time Detection for Earthquakes Based on Stacked Denoising Autoencoder

The accurate detection of P-wave arrival time is imperative for determining the hypocenter location of an earthquake. However, precise detection of onset time becomes more difficult when the signal-to-noise ratio (SNR) of the seismic data is low, such as during microearthquakes. In this letter, a stacked denoising autoencoder (SDAE) is proposed to smooth the background noise. The SDAE acts as a denoising filter for the seismic data. In the proposed algorithm, the SDAE is utilized to reduce background noise such that the onset time becomes more clear and sharp. Afterward, a hard decision with one threshold is used to detect the onset time of the event. The proposed algorithm is evaluated on both synthetic and field seismic data. As a result, the proposed algorithm outperforms the short-time average/long-time average and the Akaike information criterion algorithms. The proposed algorithm accurately picks the onset time of 94.1% for 407 field seismic waveforms with a standard deviation error of 0.10 s. In addition, the results indicate that the proposed algorithm can pick arrival times accurately for weak SNR seismic data with SNR higher than −14 dB.

DSP-based voice activity detection and background noise reduction

These days’ speech processing devices like voice-controlled devices, radio, and cell phones have gained more popularity in the area of military, audio forensics, speech recognition, education and health sectors. In the real world, speech signal during communication always contains background noise. The main task of speech related applications is voice activity detection (VAD) which include speech communication, speech recognition, and speech coding. Noise-reduction schemes for speech communication may increase the quality of speech and improve working efficiency in military aviation. Most of the developed algorithms can improve the quality of speech but unable to remove the background noise from the speech. This study provides researchers with a summary of the challenges in speech communication with background noise and provides research directions in the area of military personnel and workforces who work in noisy environments. Results of the study reveal that the DSP-based voice activity detection and background noise reduction algorithm reduced the spurious values of the speech signal.

Study of Voice Disorders Among School Teachers in Goa.

Teachers are heavy voice users, and they suffer from voice problems more frequently than other occupational voice users. Various studies have demonstrated that teachers speak longer than other professionals and that school teachers in particular, are at risk for voice problems such as vocal fatigue and vocal nodules. The present study is undertaken to study the prevalence of voice disorders in the teachers in different schools at any time and accesses the relationship of different working conditions like class room size, background noise, number of hours taught every day and role of chalk allergy in development of these voice disorders. The study was carried out on 133 school teachers with self reporting of voice problems through detailed questionnaire. A significant number of teachers, more so females had voice problems attributed to various factors. Voice amplification and reduction of background noise along with measures to control allergy are suggested.

P01.091 A robust method for rapidly simulating TTFields distributions within patient-specific computational head models

Tumor Treating Fields (TTFields) are delivered to the brain through two pairs of transducer arrays placed on the patient’s scalp. TTFields distribution in the brain depends on the array’s position, patient anatomy and the electric properties of the tissues and tumor. We aim to create realistic computational patient models in order to understand how field distribution influences disease progression. However, preparation of such models is a highly time consuming task. In addition, in clinical scenarios, MRI acquisition time is often reduced by increased slice spacing, limited field of view, or increased scan speed, leading to difficulties in creating automated models. Our method is designed to enable model creation under those restrictions. It does so by using a realistic head model of a healthy individual used as a deformable template with which the patient model is derived. A highly detailed healthy head model serves as a deformable template from which patient models are created. The first step is pre-processing, involving denoising and background noise reduction, as well as super-resolution algorithms when needed. To create the patient model, the tumor is first segmented manually and masked, leaving only healthy tissues in the MRI, which is then registered to the template space to yield the transformation from patient space to template space. The template is then deformed into the patient space using the inverse transformation, and the tumor is placed back creating a full patient model. Next, automatic identification of landmarks on the patient’s head is used to position the transducer arrays on the head, which are then introduced into the model. Finally, boundary conditions are set, and field distribution is simulated using Finite Differences Time Domain (FDTD) method (Sim4Life V3.0, ZMT-Zurich). We have simulated TTFields distribution of 317 patients treated with TTFields as part of the EF-14 trial. Our method is optimized for accurate contouring of tissues highly influencing the distribution of electric field (Scalp, skull, CSF, ventricles), and it is robust, having the ability to give sufficient results even when MRI data quality is low. Thus enabling a study correlating the spatial distribution of TTFields and patient outcome. Our process for rapidly creating patient models presents a breakthrough that enables the first study in which the spatial distribution of therapeutic electric fields correlates with patient outcome. In the future this method can be used for clinical studies investigating other clinical indications of large datasets.

Characterization and reduction of background noise for the detection of plastic anti-personnel landmine in mineralized soil

If the continuous-wave electromagnetic induction (EMI) method is used to detect plastic anti-personnel (PAP) landmines in strongly mineralized soil, background noise may interfere with and further submerge the weak secondary field generated by the landmine. To analyze quantitatively the characteristics of this noise, a semi-space homogenous medium model was developed based on a cylindrical coordinate system. The results of simulation show that, in the signal of the background noise generated by the mineralized soil, the real component dominates whereas the imaginary component is insensitive to changes in the electromagnetic properties and sensor height. A noise reduction method based on the quadrature electromagnetic method is proposed. Assuming a spherical model for the ferromagnetic components of the PAP landmine, an optimal excitation frequency of the primary field was determined. By considering the phase shift in the sensor and signal processing circuit, a method was developed to determine a sensor pre-correction. In addition, an experimental platform was built that included a PCB-based double-D EMI sensor, a data acquisition card, and a three-dimensional scanning slideway. Experimental tests with a PAP landmine buried in clay, laterite, and magnetite produced results that corroborated the above theoretical analysis. The quadrature electromagnetic method is still able to detect secondary fields with high signal-to-noise ratio generated by the PAP landmine buried 15 cm deep in the magnetite.