Estimation Of Spatial Resolution Research Articles

Determining the Feasibility of Applying Existing Criteria for Solving Operational Problems in the Design of CCTV Information Systems

Comparative analysis of the criteria for designing video surveillance information systems was conducted based on international and national CCTV standards. Their greatest differences concern identification and recognition tasks, and the smallest -– monitoring and detection. A comprehensive analysis of the impact of the technical characteristics of video cameras on the results of solving CCTV operational problems has not been carried out at this time. Therefore, the current direction of research is to determine the maximum feasibility of using the formed set of criteria. Increasing the resolution of video cameras leads to an increase in the number of pixels per meter of linear field of view. This in turn improves the display quality of the surveillance object at a greater distance from the camera. With the emergence of new information technologies, the resolution of matrices in video surveillance systems will increase. It will lead to qualitative and quantitative changes in the established set of criteria for designing of CCTV information systems. The methodology of estimation of spatial resolution of images of video surveillance information systems (CCTV) is presented in this work. The theoretical foundations for analyzing a set of technical characteristics of video cameras are confirmed by the results of computer modeling using specialized software "IP Video System Design Tool". The overall discrepancy between the calculated and modeled data does not exceed 3%. As a result, it was found that the use of a 25 MP video camera satisfies and exceeds all currently existing criteria for designing CCTV information systems for solving various types of operational tasks and the possibility of human vision. Therefore, with the cheapening and widespread use of video cameras with a resolution of over 25 MP, it will be necessary to review the feasibility of using existing criteria for designing CCTV information systems.

Retinal Ganglion Cell Topography and Spatial Resolution in Three Indian Pteropodid Bats

Pteropodidae is the only phytophagous bat family that predominantly depends on visual and olfactory cues for orientation and foraging. During daytime, pteropodids of different species roost in sites with varying light exposure. Pteropodids have larger eyes relative to body size than insectivorous bats. Retinal topography has been studied in less than 10% of the approximately 200 pteropodid species, a behavioural estimation of spatial resolution is available only for Pteropus giganteus, and little is known about the relationship between their roost site preference and visual ecology. We present retinal ganglion cell topographic maps and anatomical estimates of spatial resolution in three southern Indian pteropodid species with different roosting preferences. Ganglion cell densities are between 1,000 and 2,000 cells/mm² in the central retina and lower in the dorsal and ventral periphery. All three species have a temporal area in the retina with peak ganglion cell densities of 4,600–6,600 cells/mm². As a result, the foliage-roosting Cynopterus sphinx and the cave-roosting Rousettus leschenaultii have similar anatomical resolution (2.7 and 2.8 cycles/degree, respectively). The anatomical estimate for the larger tree-roosting P. giganteus (4.0 cycles/degree) is higher than the spatial resolution determined earlier in behavioural tests. Like other pteropodids and unlike other vertebrates, all three species have choroidal papillae. Based on 15 pteropodid species studied to date, we find no relationship between roost type and eye size or visual acuity. For a general understanding of the sensory ecology of pteropodids that perform key ecosystem services in the tropics, it will be essential to study additional species.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PurposeA novel phantom‐imaging platform, a set of software tools, for automated and high‐precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed.MethodsThe key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife‐edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate μ‐map for PET/MR systems with a robust alignment based on two‐stage image registration using specifically designed PET templates. The proposed platform is based on the open‐source NiftyPET software package used to generate multiple list‐mode data bootstrap realizations and image reconstructions to determine the precision of the two‐stage registration and any image‐derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift‐invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV.ResultsThe utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1–2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two‐stage registration.ConclusionsWe demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Measuring Image Resolution in Ultrasound Localization Microscopy.

The resolution of an imaging system is usually determined by the width of its point spread function and is measured using the Rayleigh criterion. For most system, it is in the order of the imaging wavelength. However, super resolution techniques such as localization microscopy in optical and ultrasound imaging can resolve features an order of magnitude finer than the wavelength. The classical description of spatial resolution no longer applies and new methods need to be developed. In optical localization microscopy, the Fourier Ring Correlation has showed to be an effective and practical way to estimate spatial resolution for Single Molecule Localization Microscopy data. In this work, we wish to investigate how this tool can provide a direct and universal estimation of spatial resolution in Ultrasound Localization Microscopy. Moreover, we discuss the concept of spatial sampling in Ultrasound Localization Microscopy and demonstrate how the Nyquist criterion for sampling drives the spatial/temporal resolution tradeoff. We measured spatial resolution on five different datasets over rodent's brain, kidney and tumor finding values between [Formula: see text] and [Formula: see text] for precision of localization between [Formula: see text] and [Formula: see text]. Eventually, we discuss from those in vivo datasets how spatial resolution in Ultrasound Localization Microscopy depends on both the localization precision and the total number of detected microbubbles. This study aims to offer a practical and theoretical framework for image resolution in Ultrasound Localization Microscopy.

Estimating Daily Actual Evapotranspiration at a Landsat-Like Scale Utilizing Simulated and Remote Sensing Surface Temperature

Actual evapotranspiration (ET) with high spatiotemporal resolution is very important for the research on agricultural water resource management and the water cycle processes, and it is helpful to realize precision agriculture and smart agriculture, and provides critical references for agricultural layout planning. Due to the impact of the clouds, weather environment, and the orbital period of optical satellite, there are difficulties in providing daily remote sensing data that are not contaminated by clouds for estimating daily ET with high spatial-temporal resolution. By improving the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM), this manuscript proposes the method to fuse high temporal and low spatial resolution Weather Research and Forecasting (WRF) model surface skin temperature (TSK) with the low temporal and high spatial resolution remote sensing surface temperature for obtaining high spatiotemporal resolution daily surface temperature to be used in the estimation of the high spatial resolution daily ET (ET_WRFHR). The distinction of this study from the previous literatures can be summarized as the novel application of the fusion of WRF-simulated TSK and remote sensing surface temperature, giving full play to the availability of model surface skin temperature data at any time and region, making up for the shortcomings of the remote sensing data, and combining the high spatial resolution of remote sensing data to obtain ET with high spatial (Landsat-like scale) and temporal (daily) resolution. The ET_WRFHR were cross-validated and quantitatively verified with MODIS ET products (MOD16) and observations (ET_Obs) from eddy covariance system. Results showed that ET_WRFHR not only better reflects the difference and dynamic evolution process of ET for different land types but also better identifies the details of various fine geographical objects. It also represented a high correlation with the ET_Obs by the R2 amount reaching 0.9186. Besides, the RMSE and BIAS between ET_WRFHR and the ET_Obs are obtained as 0.77 mm/d and −0.08 mm/d respectively. High R2, as well as the small RMSE and BIAS amounts, indicate that ET_WRFHR has achieved a very good performance.

Depth-Profiling Buried Interfaces within Polymer Electrolyte Membranes

Confocal Raman microscopy is being adapted to probe interfaces within bipolar membranes and ionomer-graphene composites of interest for use in fuel cell and related electrochemical devices [1-2]. Although versatile and adaptable to in-situ measurements, confocal Raman microscopy depth-profiling has pitfalls when applied to bulk membranes. Optical aberration and sensitivity to light scattering from sample regions outside the probe beam focus limit depth resolution. With these constraints in mind, initial studies focused on detecting single layer graphene (SLG) as a barrier between two Nafion membranes (Nafion 211, 25 µm thickness). These graphene-sandwich membranes have shown high selectivity for proton transport across electrochemical cells [2]. Using a microscope equipped with oil-immersion optics to provide refractive index matching, the graphene layer was easily detected in confocal Raman microscopy depth-profiles. Spectra were sensitive to defects and stress within the buried graphene layer. Building on the ability to probe membrane-supported SLG, SLG adsorbed to a glass microscope coverslip (SLG/SiO2) was adapted as a platform for confocal aperture alignment and probe volume characterization [1]. Using SLG/SiO2to estimate the limiting axial spatial resolution, the junction separating the AEM/CEM (anion exchange membrane / cation exchange membrane) phases of bipolar polymer membrane (Fumasep FBM) was probed and shown to be consistent with roughness at the boundary on the order of a few micrometers (~3 µm). Continuing efforts are aimed at developing 2-dimensional (x-, y-direction) Raman spatial maps of buried polymer membrane interfaces and model AEM/CEM interfaces for high spatial resolution (< 10 nm) neutron reflectometry depth profiling. 1. Korzeniewski, C.; Kitt, J.P.; Bukola, S.; Creager, S.E.; Minteer, S.D.; Harris, J.M. ”Single layer graphene for estimation of axial spatial resolution in confocal Raman microscopy depth profiling” Anal. Chem.2019, 91, 1049 (DOI:10.1021/acs.analchem.8b04390).2. Bukola, S.; Liang, Y.; Korzeniewski, C.; Harris, J.M.; Creager, S.E. “Selective proton / deuteron transport through Nafion | graphene | Nafion sandwich structures at very high current density” J. Am. Chem. Soc. 2018, 140, 1743. (DOI: 10.1021/jacs.7b10853)

Experimental estimation of temporal and spatial resolution of coefficient of heat transfer in a channel using inverse heat transfer method

In this research, a novel method to investigate the transient heat transfer coefficient in a channel is proposed, in which the water flow, itself, is considered both single-phase and two-phase. The experiments were designed to predict the temporal and spatial resolution of the Nusselt number. The inverse technique method is non-intrusive, in which time history of temperature is measured, using some thermocouples within the wall to provide input data for the inverse algorithm. The Tikhonov method is used as an inverse method. Error for estimation heat flux is around 0.06q mean. The temporal and spatial changes of heat flux, Nusselt number, vapor quality, convection number, and boiling number have all been estimated, showing that the estimated local Nusselt numbers of flow for without and with phase change are close to those predicted previously. This study suggests that the extended inverse technique can be successfully utilized to calculate the local time-dependent heat transfer coefficient of boiling flow.

Benchmarking spatial resolution in electronic imaging for potential in-situ Electron Beam Melting monitoring

Electron Beam Melting (EBM) is an increasingly used Additive Manufacturing (AM) technique employed by many industrial sectors, including the medical device and aerospace industries. In-situ EBM monitoring for quality assurance purposes has been a popular research area. Electronic imaging has recently been investigated as one of the in-situ EBM data collection methods, alongside thermal / optical imaging techniques. So far, the disseminations focus on the design of an electronic imaging system and the ability to generate electronic images in-situ, experiments are yet to be carried out to benchmark one of the most important features of any imaging systems – spatial resolution. This article addresses this knowledge gap by: (1) proposing an indicator for the estimation of spatial resolution which includes the Backscattered Electrons (BSE) information depth, (2) estimating the achievable spatial resolution when electronic imaging is carried out inside an Arcam A1 EBM machine, and (3) presenting an experimental method to conduct a knife edge test with the EBM machine. Analyses of experimental results indicated that the spatial resolution was of the order of 0.3 to 0.4 mm when electronic imaging was carried out at room temperature. It is believed that by disseminating an analysis and experimental method to estimate and quantify spatial resolution, this study has contributed to the on-going quality assessment research in the field of in-situ monitoring of the EBM process.

(Invited) Confocal Raman Microscopy in the Study of Membrane Materials for Energy Conversion

Confocal Raman microscopy techniques are being adapted for quantitation, structural characterization and spatial profiling in the development of materials for electrochemical energy conversion. This presentation will discuss applications to fuel cell catalytic membranes and bipolar membranes and strategies for estimation of the limiting spatial resolution in depth profiling.1,2 In the study of catalytic membranes, experiments have focused on steps in the processing of electrodes containing biocatalyst. Confocal Raman microscope measurements confirm the presence of entrapped enzymes within dispersion cast membranes and enable charge compensating mobile ions and protein to be quantified. For the enzyme laccase, a common biofuel cell O2reduction catalyst, features associated with ligands coordinating the T1 copper center are present between 400 cm-1- 500 cm-1 and provide a possible route to interrogate mechanistic chemistry at the active site of laccase biocathodes under fuel cell reaction conditions. Using a similar experimental approach, the junction connecting the anion exchange and cation exchange phases of a bipolar membrane was spatially profiled. The transition region separating the phases was broader than the limiting axial spatial resolution of the instrument, consistent with known roughness and inhomogeneity at the boundary on the order of a few micrometers. Strong Raman scattering from perchlorate enabled its use as a probe for mobile ions in the anion-exchange phase. Self-modeling curve resolution applied to spectral datasets within a depth profile enhanced spatial resolution and confirmed perchlorate ions track the spatial distribution of the AEM phase. 1Cai, R.; Abdellaouia, S.; Kitt, J.P.; Harris, J.M.; Minteer, S.D.; Korzeniewski, C. “Confocal Raman Microscopy for the Determination of Protein and Quaternary Ammonium Ion Loadings in Biocatalytic Membranes for Electrochemical Energy Conversion and Storage” Anal. Chem.(2017) 89, 13290-13298. DOI: 10.1021/acs.analchem.7b03380. 2Korzeniewski, C.; Kitt, J.P.; Bukola, S.; Creager, S.E.; Minteer, S.D.; Harris, J.M. ”Single layer graphene for estimation of axial spatial resolution in confocal Raman microscopy depth profiling” Anal. Chem. (DOI:DOI: 10.1021/acs.analchem.8b04390).

Quantifying the Effectiveness of Patterning, Test Conditions, and DIC Parameters for Characterization of Plastic Strain Localization

Digital image correlation, commonly referred to as DIC, enables full-field measurements of displacements and strains from a surface of interest. While DIC offers major advantages over commonly established methods, such as strain gauges or extensometers, some questions remain in guaranteeing data precision of the DIC measurements. This paper reports on improvements in the precision of DIC measurements of large deformations in copper tensile specimens by optimized patterning and lighting conditions, as well as quantifying the improvements in the data. In the context of detection of strain localization at welds in copper canisters for spent nuclear fuel disposal, the trade-off between spatial resolution and strain resolution is critical. To quantify the improvements in measurement conditions, we propose a method for estimation of spatial resolution and noise level of a full-field strain measurement, which does not require imposing a displacement field with variations in strain or displacement of well-defined length scale.

Standardized Estimation of Spatial Resolution of Confocal Raman Imaging

Standardized Estimation of Spatial Resolution of Confocal Raman Imaging

Single Layer Graphene for Estimation of Axial Spatial Resolution in Confocal Raman Microscopy Depth Profiling.

Single layer graphene (SLG), with its angstrom-scale thickness and strong Raman scattering cross section, was adapted for measurement of the axial ( Z-direction) probe beam profile in confocal Raman microscopy depth-profiling experiments. SLG adsorbed to a glass microscope coverslip (SLG/SiO2) served as a platform for the estimation of axial spatial resolution. Profiles were measured by stepping the confocal probe volume through the SLG/SiO2 interface while measuring Raman scattering from the sample. Using a high numerical aperture (1.4 NA) oil immersion objective, axial profiles were derived from the graphene 2D vibrational mode and fit to a Lorentzian instrument response function (IRF). Subsequently, the Z-direction spatial resolution in depth-profiling studies of polymer interfaces was estimated through convolution of the Lorentzian IRF with a step function representing the ideal junction separating the phases of interest. In the study of a bipolar polymer membrane, confocal Raman depth profiles of the AEM/CEM (anion exchange membrane/cation exchange membrane) interface show that the transition region is broader than the limiting response and are consistent with roughness at the boundary on the order of a few micrometers. Using ClO4- as a Raman active mobile ion probe, application of self-modeling curve resolution (SMCR) to spectral data sets within a profile showed ClO4- ions track the spatial distribution of the AEM phase. Finally, in measurements on a liquid-solid interface formed between 1-octanol and a polydimethylsiloxane (PDMS) membrane, the IRF derived from fitting the experimental profile was slightly narrower than those obtained from profiling SLG, indicating the potential to use polymer-liquid interfaces formed from widely available materials and reagents for estimation of axial spatial resolution in confocal Raman depth-profiling.

Predicting image properties in penalized-likelihood reconstructions of flat-panel CBCT.

Model-based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods exhibit data-dependent and shift-variant properties. Image quality predictors have been derived to prospectively estimate local noise and spatial resolution, facilitating both system hardware design and tuning of reconstruction methods. However, current MBIR image quality predictors rely on idealized system models, ignoring physical blurring effects and noise correlations found in real systems. In this work, we develop and validate a new set of predictors using a physical system model specific to flat-panel cone-beam CT (FP-CBCT). Physical models appropriate for integration with MBIR analysis are developed and parameterized to represent nonidealities in FP projection data including focal spot blur, scintillator blur, detector aperture effect, and noise correlations. Flat-panel-specific predictors for local spatial resolution and local noise properties in PL reconstructions are developed based on these realistic physical models. Estimation accuracy of conventional (idealized) and FP-specific predictors is investigated and validated against experimental CBCT measurements using specialized phantoms. Validation studies show that flat-panel-specific predictors can accurately estimate the local spatial resolution and noise properties, while conventional predictors show significant deviations in the magnitude and scale of the spatial resolution and local noise. The proposed predictors show accurate estimations over a range of imaging conditions including varying x-ray technique and regularization strength. The conventional spatial resolution prediction is sharper than ground truth. Using conventional spatial resolution predictor, the full width at half maximum (FWHM) of local point spread function (PSF) is underestimated by 0.2 mm. This mismatch is mostly eliminated in FP-specific prediction. The general shape and amplitude of local noise power spectrum (NPS) FP-specific predictions are consistent with measurement, while the conventional predictions underestimated the noise level by 70%. The proposed image quality predictors permit accurate estimation of local spatial resolution and noise properties for PL reconstruction, accounting for dependencies on the system geometry, x-ray technique, and patient-specific anatomy in real FP-CBCT. Such tools enable prospective analysis of image quality for a range of goals including novel system and acquisition design, adaptive and task-driven imaging, and tuning of MBIR for robust and reliable behavior.

Spatial Resolution and Noise Prediction in Flat-Panel Cone-Beam CT Penalized-likelihood Reconstruction.

Model based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods have data-dependent and shift-variant image properties. Predictors of local reconstructed noise and resolution have found application in a number of methods that seek to understand, control, and optimize CT data acquisition and reconstruction parameters in a prospective fashion (as opposed to studies based on exhaustive evaluation). However, previous MBIR prediction methods have relied on idealized system models. In this work, we develop and validate new predictors using accurate physical models specific to flat-panel CT systems. Novel predictors for estimation of local spatial resolution and noise properties are developed for PL reconstruction that include a physical model for blur and correlated noise in flat-panel cone-beam CT (CBCT) acquisitions. Prospective predictions (e.g., without reconstruction) of local point spread function and and local noise power spectrum (NPS) model are applied, compared, and validated using a flat-panel CBCT test bench. Comparisons between prediction and physical measurements show excellent agreement for both spatial resolution and noise properties. In comparison, traditional prediction methods (that ignore blur/correlation found in flat-panel data) fail to capture important data characteristics and show significant mismatch. Novel image property predictors permit prospective assessment of flat-panel CBCT using MBIR. Such predictors enable standard and task-based performance assessments, and are well-suited to evaluation, control, and optimization of the CT imaging chain (e.g., x-ray technique, reconstruction parameters, novel data acquisition methods, etc.) for improved imaging performance and/or dose utilization.

SPATIAL RESOLUTION ASSESSMENT OF THE TELOPS AIRBORNE TIR IMAGERY

Abstract. Having a high spatial resolution of Thermal InfraRed (TIR) Sensors is a challenge in remote sensing applications. Airborne high spatial resolution TIR is a novel source of data that became available lately. Recent developments in spatial resolution of the TIR sensors have been an interesting topic for scientists. TIR sensors are very sensitive to the energies emitted from objects. Past researches have been shown that increasing the spatial resolution of an airborne image will decrease the spectral content of the data and will reduce the Signal to Noise Ratio (SNR). Therefore, in this paper a comprehensive assessment is adapted to estimate an appropriate spatial resolution of the TIR data (TELOPS TIR data), in consideration of the SNR. So, firstly, a low-pass filter is applied on TIR data and the achieved products fed to a classification method for analysing of the accuracy improvement. The obtained results show that, there is no significant change in classification accuracy by applying low-pass filter. Furthermore, estimation of the appropriate spatial resolution of the TIR data is evaluated for obtaining higher spectral content and SNR. For this purpose, different resolutions of the TIR data are created and fed to the maximum likelihood classification method separately. The results illustrated in the case of using images with ground pixel size four times greater than the original image, the classification accuracy is not reduced. Also, SNR and spectral contents are improved. But the corners sharpening is declined.

Application of hourly radar-gauge merging method for quantitative precipitation estimates

Gridded quantitative precipitation estimation (QPE) of high spatial and temporal resolution is now being increasingly used for instance for hydrological modelling. The combination between observations from radar data and in-situ rain-gauge measurement is a popular mean to produce QPEs. Since the QPE generated from radar data only is considered to be not satisfactory, some corrections should be introduced in order to achieve better accuracy of the instant precipitation estimation. The correction method that were used were Mean Field Bias Correction (MFB) and static adjustment. MFB was applied by the assumption that the radar estimation was affected by uniform multiplicative error. The static adjustment was applied to correct radar rainfall data through plotting between radar rainfall and rain gauge so that the regression line between radar and rain gauge was approaching one. The purpose of radar QPE corrections was for hydrological modelling applications.

2A2-U02 足裏画像を用いた画像処理による足圧分布推定手法

This paper presents the new method that calculate the plantar pressure distribution based on the brightness distribution of the continuous plantar image captured by the camera located under a transparent acrylic resin plate. To evaluate the proposed method, the comparison experiments are conducted with the hemisphere model that simulated a human heel. The measurement result by the proposed method and the pressure sensor while the model pushed down with the same vertical force are compared. The experimental results show that pressure distribution calculated by the proposed method are qualitatively similar to pressure distribution by the existing sensor. The intensity of brightness of the contacting area changes according to the pushed vertical force. The resolution of the camera that we use are three orders of magnitude higher than the existing sensor. The experimental results suggested the possibility of estimation of the high spatial resolution of the dynamic plantar pressure distribution.

红外动态场景生成装置空间分辨率的测试

红外动态场景生成装置空间分辨率的测试

Angular sensitivity and spatial resolution in edge illumination X-ray phase-contrast imaging

Edge illumination (EI) is an X-ray phase-contrast imaging (XPCi) technique which bears high potential for applications in several fields, thanks to its simple experimental setup and to its applicability with conventional X-ray sources. In this context, the estimation of the phase sensitivity and spatial resolution achievable with EI is of particular importance, as it will enable assessing and quantifying the full potential of the technique. We present in this article a simple theoretical model that allows the analysis of these two quantities and of their dependence upon the different acquisition parameters. We believe that the obtained results will prove very useful for the design and optimization of future setups. Besides, we demonstrate experimentally that the simplicity of the EI setup does not come at the expense of the sensitivity; on the contrary, EI allows achieving very high angular resolutions.

A feasibility study of PETiPIX: an ultra high resolution small animal PET scanner

PETiPIX is an ultra high spatial resolution positron emission tomography (PET) scanner designed for imaging mice brains. Four Timepix pixellated silicon detector modules are placed in an edge-on configuration to form a scanner with a field of view (FoV) 15 mm in diameter. Each detector module consists of 256 × 256 pixels with dimensions of 55 × 55 × 300 μm3. Monte Carlo simulations using GEANT4 Application for Tomographic Emission (GATE) were performed to evaluate the feasibility of the PETiPIX design, including estimation of system sensitivity, angular dependence, spatial resolution (point source, hot and cold phantom studies) and evaluation of potential detector shield designs. Initial experimental work also established that scattered photons and recoil electrons could be detected using a single edge-on Timepix detector with a positron source. Simulation results estimate a spatial resolution of 0.26 mm full width at half maximum (FWHM) at the centre of FoV and 0.29 mm FWHM overall spatial resolution with sensitivity of 0.01%, and indicate that a 1.5 mm thick tungsten shield parallel to the detectors will absorb the majority of non-coplanar annihilation photons, significantly reducing the rates of randoms. Results from the simulated phantom studies demonstrate that PETiPIX is a promising design for studies demanding high resolution images of mice brains.