Ricardo J. Colom

PESIC: An Integrated Front-End for PET Applications

An ASIC front-end has been developed for multi-anode photomultiplier based nuclear imaging devices. Its architecture has been designed to improve resolution and decrease pile-up probability in Positron Emission Tomography systems which employ continuous scintillator crystals. Analog computation elements are isolated from the photomultiplier by means of a current sensitive preamplifier stage. This allows digitally programmable adjustment of every anode gain, also providing better resolution in gamma event position calculation and a shorter front-end deadtime. The preamplifier stage also offers the possibility of using other types of photomultiplier devices such as SiPM. The ASIC architecture includes measurement of the depth of interaction of the gamma event based on the width of the light distribution in order to reduce parallax error and increase spatial resolution during image reconstruction stage. An output stage of transresistance amplifiers offer voltage output signals which may be introduced in the A/D conversion stage with no further processing.

Evolutionary continuous cellular automaton for the simulation of wet etching of quartz

Anisotropic wet chemical etching of quartz is a bulk micromachining process for the fabrication of micro-electro-mechanical systems (MEMS), such as resonators and temperature sensors. Despite the success of the continuous cellular automaton for the simulation of wet etching of silicon, the simulation of the same process for quartz has received little attention—especially from an atomistic perspective—resulting in a lack of accurate modeling tools. This paper analyzes the crystallographic structure of the main surface orientations of quartz and proposes a novel classification of the surface atoms as well as an evolutionary algorithm to determine suitable values for the corresponding atomistic removal rates. Not only does the presented evolutionary continuous cellular automaton reproduce the correct macroscopic etch rate distribution for quartz hemispheres, but it is also capable of performing fast and accurate 3D simulations of MEMS structures. This is shown by several comparisons between simulated and experimental results and, in particular, by a detailed, quantitative comparison for an extensive collection of trench profiles.

DOI measurement with monolithic scintillation crystals: A primary performance evaluation

We report a first assessment of image quality enhancement achieved by the implementation of depth of interaction detection with monolithic crystals. The method of interaction depth measurement is based on analogue computation of the standard deviation with an enhanced charge divider readout. This technique of depth of interaction detection was developed in order to provide fast and determination of this parameter at a reasonable increase of detector cost. The detector consists of an large-sized monolithic scintillator coupled to a position sensitive photomultiplier tube. A special design feature is the flat-topped pyramidal shape of the crystal. This reduces image compression near the edges of the scintillator. We studied the image enhancement qualitatively with a FDG filled hot spot phantom and quantitatively by displacing a single point source along a radial axis. An important uniformity improvement was observed for the reconstructed image of the hot spot phantom when depth of interaction correction was applied. A moderate improvement of the spatial resolution was observed when reconstructing the images of the point source with depth of interaction correction.

Implementation and evaluation of the Level Set method: Towards efficient and accurate simulation of wet etching for microengineering applications

Abstract The use of atomistic methods, such as the Continuous Cellular Automaton (CCA), is currently regarded as a computationally efficient and experimentally accurate approach for the simulation of anisotropic etching of various substrates in the manufacture of Micro-electro-mechanical Systems (MEMS). However, when the features of the chemical process are modified, a time-consuming calibration process needs to be used to transform the new macroscopic etch rates into a corresponding set of atomistic rates. Furthermore, changing the substrate requires a labor-intensive effort to reclassify most atomistic neighborhoods. In this context, the Level Set (LS) method provides an alternative approach where the macroscopic forces affecting the front evolution are directly applied at the discrete level, thus avoiding the need for reclassification and/or calibration. Correspondingly, we present a fully-operational Sparse Field Method (SFM) implementation of the LS approach, discussing in detail the algorithm and providing a thorough characterization of the computational cost and simulation accuracy, including a comparison to the performance by the most recent CCA model. We conclude that the SFM implementation achieves similar accuracy as the CCA method with less fluctuations in the etch front and requiring roughly 4 times less memory. Although SFM can be up to 2 times slower than CCA for the simulation of anisotropic etchants, it can also be up to 10 times faster than CCA for isotropic etchants. In addition, we present a parallel, GPU-based implementation (gSFM) and compare it to an optimized, multicore CPU version (cSFM), demonstrating that the SFM algorithm can be successfully parallelized and the simulation times consequently reduced, while keeping the accuracy of the simulations. Although modern multicore CPUs provide an acceptable option, the massively parallel architecture of modern GPUs is more suitable, as reflected by computational times for gSFM up to 7.4 times faster than for cSFM.

Design and Calibration of a Small Animal Pet Scanner Based on Continuous LYSO Crystals and PSPMTs

We report on the design of a small animal PET scanner based on continuous LYSO crystals and position sensitive photomultiplier tubes (PSPMTs), together with the first results from the calibration. The scanner consists of eight compact modules forming an octagon and leaving a port of 110 mm aperture. Each module is made out of a continuous LYSO crystal and a PSPMT, and contains its associated electronics together with its power supply. For each module, five signals are read, summarizing all the information coming out from its 64 anode pads. Therefore, for the whole scanner only 40 signals are digitized. A calibration procedure has been implemented, measuring a spatial resolution of approximately 1.5 mm at the center of the field of view and an energy resolution of 18%. The sensitivity of the system at the center of the field of view, using only 4 modules, is observed to be of about 1%.

Level set implementation for the simulation of anisotropic etching: Application to complex MEMS micromachining

This work has been supported by the Spanish FPI-MICINN BES-2011-045940 grant and the Ramon y Cajal Fellowship Program by the Spanish Ministry of Science and Innovation. Also, we acknowledge support by the JAE-Doc grant from the Junta para la Ampliacion de Estudios program co-funded by FSE and the Professor Partnership Program by NVIDIA Corporation.

FPGA Custom DSP for ECG Signal Analysis and Compression

This work describes a Virtex-II implementation of a custom DSP for QRS-Complex detection, ECG signal analysis and data compression for optimum transmission and storage. For QRS-Complex detection we introduce a custom architecture based on a modification of the Hamilton-Tompkins (HT) algorithm oriented to area saving. We also use biorthogonal wavelet transform for ECG signal compression and main ECG parameters estimation. In contrast with previously published works, our modified version of the HT algorithm offers best performance (a 99% of QRS-detection over normalized noisy ECGs). Moreover, a compression ratio of 20:1 is obtained when the wavelet-based engine is running. Results have been successfully verified by using a combination of MATLAB with SystemGen, Modelsim and a FPGA PCI-based Card (AlphaData ADM-XRC-II). The QRS-complex detector and compressor requires minimum area resources in term of LUT and registers, allowing a custom DSP as coprocessor in a SoC for biomedical applications.

A mixed hardware-software approach to flexible Artificial Neural Network training on FPGA

FPGAs offer a promising platform for the implementation of Artificial Neural Networks (ANNs) and their training, combining the use of custom optimized hardware with low cost and fast development time. However, purely hardware realizations tend to focus on throughput, resorting to restrictions on applicable network topology or low-precision data representation, whereas flexible solutions allowing a wide variation of network parameters and training algorithms are usually restricted to software implementations. This paper proposes a mixed approach, introducing a system-on-chip (SoC) implementation where computations are carried out by a high efficiency neural coprocessor with a large number of parallel processing elements. System flexibility is provided by on-chip software control and the use of floating-point arithmetic, and network parallelism is exploited through replicated logic and application-specific coprocessor architecture, leading to fast training time. Performance results and design limitations and trade-offs are discussed.

Expandable programmable integrated front-end for scintillator based photodetectors

Scintillator based photodetectors tend to increase the number of output signals in order to improve spatial and energy resolutions. AMIC architecture was introduced in previous works as an alternative to traditional charge division front-ends. This novel architecture not only allowed to reduce the number of signals to be acquired but also provided more information about the light distribution on the photodetector surface. Another key feature of this new approach lies in its ability to manage any number of inputs, thus offering an expandable solution for photodetectors with a large number of output signals. The underlying idea in AMIC architecture is to calculate the moments of the detected light distribution in an analog fashion. Due to the additive nature of the moment calculation, the operation can be carried out on a single device or split it into several devices, adding the partial results afterwards. A new integrated front-end device AMIC2GR has been developed which improves several features of the original AMIC architecture. A new preamplifier configuration extends the maximum capacitive load thus allowing compatibility with many types of photomultipliers including SiPM without loss of performance. In order to test the expandability of AMIC architecture using the new AMIC2GR, a front end with 4 devices has been developed. Measurements with a 256-SiPM array were made. Furthermore, a new calibration method (Edna Calibration Method) to compensate gain and detector module differences was developed and tested. AMIC2GR allows to calibrate each SiPM individually to obtain better spatial resolution and homogeneity.

Development of a Spectrophotometric System to Detect White Striping Physiopathy in Whole Chicken Carcasses

Due to the high intensification of poultry production in recent years, white chicken breast striping is one of the most frequently seen myopathies. The aim of this research was to develop a spectrophotometry-based sensor to detect white striping physiopathy in chicken breast meat in whole chicken carcasses with skin. Experiments were carried out using normal and white striping breasts. In order to understand the mechanism involved in this physiopathy, the different tissues that conform each breast were analyzed. Permittivity in radiofrequency (40 Hz to 1 MHz) was measured using two different sensors; a sensor with two flat plates to analyze the whole breast with skin (NB or WSB), and a two needles with blunt-ended sensor to analyze the different surface tissues of the skinless breast. In the microwave range (500 MHz to 20 GHz), permittivity was measured as just was described for the two needles with blunt-ended sensor. Moreover, fatty acids composition was determined by calorimetry techniques from −40 °C to 50 °C at 5 °C/min after previously freeze-drying the samples, and pH, microstructure by Cryo-SEM and binocular loupe structure were also analyzed. The results showed that the white striping physiopathy consists of the partial breakdown of the pectoral muscle causing an increase in fatty acids, reducing the quality of the meat. It was possible to detect white striping physiopathy in chicken carcasses with skin using spectrophotometry of radiofrequency spectra.