Proton-counting radiography for proton therapy: a proof of principle using CMOS APS technology

Despite the early recognition of the potential of proton imaging to assist proton therapy (Cormack 1963 J. Appl. Phys. 34 2722), the modality is still removed from clinical practice, with various approaches in development. For proton-counting radiography applications such as computed tomography (CT), the water-equivalent-path-length that each proton has travelled through an imaged object must be inferred. Typically, scintillator-based technology has been used in various energy/range telescope designs. Here we propose a very different alternative of using radiation-hard CMOS active pixel sensor technology. The ability of such a sensor to resolve the passage of individual protons in a therapy beam has not been previously shown. Here, such capability is demonstrated using a 36 MeV cyclotron beam (University of Birmingham Cyclotron, Birmingham, UK) and a 200 MeV clinical radiotherapy beam (iThemba LABS, Cape Town, SA). The feasibility of tracking individual protons through multiple CMOS layers is also demonstrated using a two-layer stack of sensors. The chief advantages of this solution are the spatial discrimination of events intrinsic to pixelated sensors, combined with the potential provision of information on both the range and residual energy of a proton. The challenges in developing a practical system are discussed

Spectral pre-modulation of training examples enhances the spatial resolution of the Phase Extraction Neural Network (PhENN)

The Phase Extraction Neural Network (PhENN) is a computational architecture, based on deep machine learning, for lens-less quantitative phase retrieval from raw intensity data. PhENN is a deep convolutional neural network trained through examples consisting of pairs of true phase objects and their corresponding intensity diffraction patterns; thereafter, given a test raw intensity pattern PhENN is capable of reconstructing the original phase object robustly, in many cases even for objects outside the database where the training examples were drawn from. Here, we show that the spatial frequency content of the training examples is an important factor limiting PhENN's spatial frequency response. For example, if the training database is relatively sparse in high spatial frequencies, as most natural scenes are, PhENN's ability to resolve fine spatial features in test patterns will be correspondingly limited. To combat this issue, we propose "flattening" the power spectral density of the training examples before presenting them to PhENN. For phase objects following the statistics of natural scenes, we demonstrate experimentally that the spectral pre-modulation method enhances the spatial resolution of PhENN by a factor of 2.Comment: 12 pages, 10 figure

An apodized-aperture x-ray detector design for improved image quality in mammography

X-ray imaging for early cancer detection, such as screening mammography, requires images with high signal-to-noise ratio (SNR) using low levels of radiation exposure. Conventional detectors consist of a matrix of sensor elements, producing images where each pixel corresponds to a single sensor element. This imposes a fundamental limitation on image contrast and SNR for imaging fine detail for a given exposure. The work presented here reconsiders x-ray image formation using a new x-ray detector design that synthesizes image pixels from a large number of very small sensor elements with the goal of optimizing contrast and SNR. Our new detector design, called apodized-aperture pixel (AAP), makes use of recent technology developments to produce images from an “over-sampled” sensor signal while suppressing both signal and noise aliasing to improve the modulation transfer function (MTF) and detective quantum efficiency (DQE). Signal and noise performance of the AAP approach is described theoretically using a cascaded-systems analysis. This approach preserves the MTF of the small sensor elements up to the image sampling cut-off frequency where the MTF is increased by up to 53%. Frequencies above the cut-off are suppressed, eliminating both signal and noise aliasing artifacts and corresponding to a high-frequency DQE increase by 2.5x. X-ray interactions in a scintillator introduce signal and noise correlations, including x-ray reabsorption and converter blur, resulting in reduced aliasing and decreased improvement in DQE. Best results with the AAP design were obtained using a high-resolution converter, such as selenium (Se), with little impact from reabsorption. Implementation on a Se/CMOS micro-sensor prototype with 7.8\mum element size with image pixel size approximately 50\mum showed a flat DQE curve (ideal) up to 10cycles/mm. AAP images of resolution test patterns, mammography phantoms, and specimen imaging of micro-calcifications from biopsies showed the expected improvements in SNR and visibility of fine-detail. It is concluded that synthesizing image pixels from small physical sensor elements can increase MTF and DQE, and eliminate aliasing artifacts, for a desired image pixel size. The resulting increase in SNR may benefit all forms of radiography, and in particular mammography, where accurate visualization of fine detail is important for early cancer detection

The SWAP EUV Imaging Telescope Part I: Instrument Overview and Pre-Flight Testing

The Sun Watcher with Active Pixels and Image Processing (SWAP) is an EUV solar telescope on board ESA's Project for Onboard Autonomy 2 (PROBA2) mission launched on 2 November 2009. SWAP has a spectral bandpass centered on 17.4 nm and provides images of the low solar corona over a 54x54 arcmin field-of-view with 3.2 arcsec pixels and an imaging cadence of about two minutes. SWAP is designed to monitor all space-weather-relevant events and features in the low solar corona. Given the limited resources of the PROBA2 microsatellite, the SWAP telescope is designed with various innovative technologies, including an off-axis optical design and a CMOS-APS detector. This article provides reference documentation for users of the SWAP image data.Comment: 26 pages, 9 figures, 1 movi

Inter-Pixel Crosstalk in Teledyne Imaging Sensors (TIS) H4RG-10 Detectors

CMOS-hybrid arrays have recently surfaced as competitive optical detectors for use in ground- and space-based astronomy. One source of error in these detectors that does not appear in more traditional CCD arrays is the inter-pixel capacitance component of crosstalk. In this paper we use a single pixel reset method to model inter-pixel capacitance (IPC). We combine this IPC model with a model for charge diffusion to estimate the total crosstalk on H4RG arrays. Finally, we compare our model results to Fe55 data obtained using an astrometric camera built to test the H4RG-B0 generation detectors.Comment: Accepted to Applied Optics 03-26-1

Large area CMOS active pixel sensor x‐ray imager for digital breast tomosynthesis: Analysis, modeling, and characterization

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134791/1/mp2368.pd