MOBILE, HYBRID COMPTON/CODED APERTURE IMAGING FOR DETECTION, IDENTIFICATION AND LOCALIZATION OF GAMMA-RAY SOURCES AT STAND-OFF DISTANCES

The Stand-off radiation detection system (SORDS) program is an advanced technology demonstration (ATD) project through the Domestic Nuclear Detection Office (DNDO) with the goal of detection, identification and localization of weak radiological sources in the presence of large dynamic backgrounds. The Raytheon-Tri-Modal Imager (TMI) is a mobile truck-based, hybrid gamma-ray spectroscopic and imaging system able to quickly detect, identify and localize, radiation sources at standoff distances through improved sensitivity provided by multiple detection modes while minimizing the false alarm rate. Reconstruction of gamma-ray sources is performed using a combination of gamma-ray spectroscopy and two imaging modalities; coded aperture and Compton scatter imaging. The TMI consists of 35 NaI crystals (5x5x2 in each), arranged in a random coded aperture CA, followed by 30 position sensitive NaI bars (24x2.5x3 in each) called the DA. The CA array acts as both a coded aperture mask and scattering detector for Compton events. The large-area DA array acts as a collection detector for both Compton scattered events and coded aperture events. In this thesis, the implemented spectroscopic, coded aperture, Compton and hybrid imaging algorithms will be described along with their performance. It will be shown that multiple imaging modalities can be fused to improve detection sensitivity over a broader energy range than any mode alone. Since the TMI is a moving system, peripheral data, such as a GPS and INS must also be incorporated. A method of adapting static imaging algorithms to a moving platform has been developed. Also, algorithms were developed in parallel with detector hardware, through the use of extensive simulations performed with the GEANT4. Simulations have been well validated against measured data. Results of image reconstruction algorithms at various speeds and distances will be presented as well as localization capability. Utilizing imaging information will show signal-to-noise gains over spectroscopic algorithms alone

A micropower vision processor for parallel object positioning and sizing

Accepted versio

A 192×128 Time Correlated SPAD Image Sensor in 40-nm CMOS Technology

A 192 X 128 pixel single photon avalanche diode (SPAD) time-resolved single photon counting (TCSPC) image sensor is implemented in STMicroelectronics 40-nm CMOS technology. The 13% fill factor, 18.4\,\,\mu \text {m} \times 9.2\,\,\mu \text{m} pixel contains a 33-ps resolution, 135-ns full scale, 12-bit time-to-digital converter (TDC) with 0.9-LSB differential and 5.64-LSB integral nonlinearity (DNL/INL). The sensor achieves a mean 219-ps full-width half-maximum (FWHM) impulse response function (IRF) and is operable at up to 18.6 kframes/s through 64 parallelized serial outputs. Cylindrical microlenses with a concentration factor of 3.25 increase the fill factor to 42%. The median dark count rate (DCR) is 25 Hz at 1.5-V excess bias. A digital calibration scheme integrated into a column of the imager allows off-chip digital process, voltage, and temperature (PVT) compensation of every frame on the fly. Fluorescence lifetime imaging microscopy (FLIM) results are presented

Optimisation and comparison of dSTORM and DNA-PAINT super-resolution for quantitative cardiac protein imaging.

Fluorescence microscopy techniques, restricted by the diffraction limit of light, have seen a remarkable advancement in recent years. An approach called dSTORM (direct stochastic optical reconstruction microscopy) utilises the photoswitching capabilities of organic fluorophores when in the presence of special mounting media, the solution within which the sample is placed, to detect single molecule fluorescing events over time. The image that can be reconstructed from these events is not diffraction limited, but instead is limited by how well each event can be precisely localised. In Chapter 3 the importance of using a suitable mounting buffer in order to achieve super-resolution dSTORM is discussed in detail. A quantitative method for determining the reactivity of thiol dSTORM switching mountants was developed for use within the lab. Every fluorescent probe has different photophysical properties which can be manipulated by varying the composition of the switching buffer to enhance desirable qualities, such as; increased photon counts, faster switching rates, and longer survivability. In addition to investigating the effects of buffer composition the use of a near UV light-source was also explored as a means of manipulating the same properties to improve overall resolution and quality of the resulting images. A range of photoswitchable fluorescent dyes were tested including Alexa Fluor 660 which is a dye that to my knowledge has not been greatly tested for use in single molecule localisation microscopy by others to date. This dye performed strongly alongside the traditional Alexa Fluor 647 used for dSTORM imaging in optimal conditions. A relatively new approach to single molecule imaging which does not require the fluorophore to photoswitch, called DNA-PAINT (point accumulation for imaging in nanoscale topography), has been investigated throughout this thesis. This approach relies on the transient binding of small oligonucleotide sequences, called “Imagers”, to target docking strands anchored in positions of interest. These imagers have a photostable and bright fluorophore conjugated to the oligonucleotide. It is the transient immobilisation of the imager strand, as it binds to a fixed docking strand, which appears as stochastic blinks. The duration of these events, which can be extended by increasing the number of overlapping base pairs, is primarily responsible for improved localisation precision and therefore potentially overall resolution. At the end of Chapter 3 I compare this new pointillism microscopy approach, DNA-PAINT, with dSTORM using a set of custom-designed oligonucleotide sequences that allow both formats to be employed on the same target. The transient binding of small strands of oligonucleotides offers a far more controllable system for stochastic imaging. In Chapter 4 I use this superior approach to achieve greater resolution than other fluorescence techniques in biological samples, sufficient to visualise single ryanodine receptors (RyR). The RyR are extremely important in the contraction of muscle cells as they are capable of detecting transient changes to calcium concentration and are responsible for releasing large stores of calcium from the sarcoplasmic reticulum. With DNA-PAINT I observed that RyRs cluster into irregular arrays which contain significant gaps that are occupied by other proteins, including junctophilin (JPH). The stoichiometry of JPH with RyR varied cluster to cluster, exposing a new complexity in the regulation of RyRs. In Chapter 5, quantitative super-resolution is reliably achieved through the implementation of quantitative DNA-PAINT (qPAINT) within the Python Microscopy Environment (PYME) software. Quantitative measurements are possible because of the statistical predictability of DNA hybridisation and the near constant influx of fresh imager strands by diffusion. This results in limited photobleaching, a permanent dark state. The frequency with which a region of interest blinks is proportional to the number of binding sites available, and therefore the mean dark time between detected events is also inversely proportional. I validate my approach to qPAINT, which maintains the spatial information of individual structures, by using a DNA-origami test slide. Two distinguishable structures were present and an estimate for the ratio of available docking sites between them was satisfactorily established. I conclude that with this tool, molecule densities can be inferred and information about biological samples can be probed to new levels. The results of the full methodological approach to accomplish dual-colour super-resolution imaging of optically thick cardiac tissue, using both dSTORM and DNA PAINT techniques, is discussed in detail in Chapter 6. The current range of photoswitchable fluorophores limits the possible combination of molecular dyes for use with dSTORM and some compromise is made in their selection. For DNA-PAINT, the prospect of chromatic aberration is removed by imaging the same dye in subsequent rounds of imaging. The process, called Exchange-PAINT, allows the user to remove previously imaged imager strands, through a series of washes, and replace them with a complementary sequence for another target. I introduce the concept of using quencher strands to eliminate signal from unwanted imager sequences, accelerating their removal in samples of reduced diffusion and decreasing the risk of sample disturbance, in a process we termed Quencher Exchange-PAINT. Using this technique, I achieve superior super resolution results in optically thick samples. The results presented in this thesis are expected to (1) lead to a better understanding of the variables associated with single molecule localisation microscopy, (2) further reveal the complexity in cardiac protein distribution, (3) quantify relationships between co-localising proteins and other targets, and (4) apply DNA-PAINT to imaging in optically thick biological samples. This study shows promise for the future applications of the DNA-PAINT pointillism super-resolution method and its ability to investigate a multitude of biological questions

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

Magnetic resonance imaging of lung cancer in the presence of respiratory motion: Dynamic keyhole and audio visual biofeedback

Breath-to-breath variations in breathing can cause image artefacts. Day-to-day variations can cause a disagreement of position and volume between planning and treatment throughout radiotherapy procedures, requiring a larger treatment margin and longer treatment time. An advanced radiotherapy system requires: (1) a fast imaging technique for the compensation of breathing variations and/or (2) a respiratory motion management technique for the control of breathing variations. A novel MRI reconstruction method called “Dynamic keyhole” was proposed as a fast imaging technique. This thesis investigated (1) the concept of this method in terms of the improvement in temporal resolution with healthy volunteer MRI datasets and (2) the applicability of real-time lung tumour localization in terms of the accuracy of tumour motion and shape with lung cancer patient MRI datasets. The dynamic keyhole method achieved an increase in imaging frequency by up to a factor of five when compared with full k-space methods whilst achieving sub-millimetre tumour motion accuracy and preserving tumour shape within 98%. AV biofeedback respiratory guidance was used for healthy volunteers and lung cancer patients. This thesis investigated the impact of AV biofeedback on (1) intra- and inter-fraction lung tumour motion using cine-MRI, (2) inter-fraction lung tumour position and intra-fraction tumour volume using breath-hold MRI and (3) the improvement in image quality and the reduction in scan time using respiratory-gated MRI. AV biofeedback respiratory guidance improved intra- and inter-fraction tumour motion and position reproducibility, and intra-fraction tumour volume consistency. In addition, it was found to improve image quality and reduce scan time. The performance of the dynamic keyhole method and AV biofeedback respiratory guidance shown in this thesis illustrates potential advantages of real-time tumour imaging and tumour motion management in the course of lung cancer radiotherapy

Smart cmos image sensor for 3d measurement

3D measurements are concerned with extracting visual information from the geometry of visible surfaces and interpreting the 3D coordinate data thus obtained, to detect or track the position or reconstruct the profile of an object, often in real time. These systems necessitate image sensors with high accuracy of position estimation and high frame rate of data processing for handling large volumes of data. A standard imager cannot address the requirements of fast image acquisition and processing, which are the two figures of merit for 3D measurements. Hence, dedicated VLSI imager architectures are indispensable for designing these high performance sensors. CMOS imaging technology provides potential to integrate image processing algorithms on the focal plane of the device, resulting in smart image sensors, capable of achieving better processing features in handling massive image data. The objective of this thesis is to present a new architecture of smart CMOS image sensor for real time 3D measurement using the sheet-beam projection methods based on active triangulation. Proposing the vision sensor as an ensemble of linear sensor arrays, all working in parallel and processing the entire image in slices, the complexity of the image-processing task shifts from O (N 2 ) to O (N). Inherent also in the design is the high level of parallelism to achieve massive parallel processing at high frame rate, required in 3D computation problems. This work demonstrates a prototype of the smart linear sensor incorporating full testability features to test and debug both at device and system levels. The salient features of this work are the asynchronous position to pulse stream conversion, multiple images binarization, high parallelism and modular architecture resulting in frame rate and sub-pixel resolution suitable for real time 3D measurements

Laser beams-based localization methods for Boom-type roadheader using underground camera non-uniform blur model

The efficiency of automatic underground tunneling is significantly depends on the localization accuracy and reliable for the Boom-type roadheader. In comparison with other underground equipment positioning methods, vision-based measurement has gained attention for its advantages of noncontact and no accumulated error. However, the harsh underground environment, especially the geometric errors brought by the vibration of the machine body to the underground camera model, has a certain influence on the accuracy and stability for the vision-based underground localization. In this paper, a laser beams-based localization methods for the machine body of Boom-type roadheader is presented, which can tackle the dense-dust, low illumination environment with the stray lights interference. Taking mining vibration into consideration, an underground camera non-uniform blur model that incorporate the two-layer glasses refraction effect was established to eliminate vibration errors. The blur model explicitly reveals the change of imaging optical path under the influence of vibration and double layer explosion-proof glass. On the basis of this, the underground laser beams extraction and positioning are presents, which is with well environmental adaptability, and the improved 2P3L (two-points-three-lines) localization model from line correspondences are developed. Experimental evaluation are designed to verify the performance of the proposed method, and the deblurring algorithm is investigated and evaluated. The results show that the proposed methods is effective to restore the blurred laser beams image that caused by the vibration, and can meet the precision need of roadheader body localization for roadway construction in coal mine