Tissue-mimicking phantoms can be used to study various diagnostic imaging techniques and image-guided therapeutic interventions. Bioprinting enables the incorporation of live cells into printed phantoms. Some advantages of bioprinted phantoms include their close similarity to in vivo condition and change in phantom composition with time as the cells proliferate and secrete the extra cellular matrix components. In this study, we 3D-print alginate to form three different types of phantoms; those containing human vascular smooth muscle cells, human liver cancer cells, and no cells, each representing benign tissue, cancer tissue, and controls, respectively. The phantoms are imaged with a clinical ultrasound scanner and Temporal Enhanced Ultrasound (TeUS) data is collected. The comparison of the power spectrum of TeUS depicts separation among the three phantom types.
Quantum-Dot Cellular Automata (QCA) is one of several proposed computational nanotechnology paradigms
that are being investigated as alternatives to CMOS at the nano-scale. QCA has been reported to offer relatively
low power consumption, and very high device density. In recent years, several researchers have started investigating
relatively complex circuit architectures using QCA. Such design efforts have highlighted the crosstalk
problem in QCA and the lack of research in this area. This paper explores the nature of crosstalk in QCA. We
show how crosstalk can be amplified due to several parameters including wire length and the distance between
adjacent cells. We develop a model and method that allows us to test for crosstalk using a set of test vectors.
We also propose a set of cell placement guidelines and design geometries that help to minimize QCA crosstalk
in large circuits.
Proc. SPIE. 4791, Advanced Signal Processing Algorithms, Architectures, and Implementations XII
KEYWORDS: Optical filters, Digital signal processing, Signal attenuation, Digital filtering, Computing systems, Finite impulse response filters, Quantization, Associative arrays, Computer architecture, Binary data
We introduce the use of multidimensional logarithmic number system (MDLNS) as a generalization of the classical 1-D logarithmic number system (LNS) and analyze its use in DSP applications. The major drawback of the LNS is the requirement to use very large ROM arrays in implementing the additions and subtraction and it limits its use to low-precision applications. MDLNS allows exponential reduction of the size of the ROMs used without affecting the speed of the computational process; moreover, the calculations over different bases and digits are completely independent, which makes this particular representation perfectly suitable for massively parallel DSP architectures. The use of more than one base has at least two extra advantages. Firstly, the proposed architecture allows us to obtain the final result straightforwardly in binary form, thus, there is no need of the exponential amplifier, used in the known LNS architectures. Secondly, the second base can be optimized in accordance to the specific digital filter characteristics. This leads to dramatic reduction of the exponents used and, consequently, to large area savings. We offer many examples showing the computational advantages of the proposed approach.