Via-Programmable Structured ASIC Fabric Based on MCML Cells: Design-Flow and Implementation

This paper presents a regular layout fabric made of via-programmable MCML universal logic cells for structured ASIC applications and the associated design flow. The proposed structured ASIC fabric offers high speed operation, very high noise immunity, as well as low production cost due to the via-programmable properties of the universal logic cell. Implementations of a number of circuits are presented and the area/speed performances are compared with classical CMOS implementation using a commercial standard cell library in 0.18 um CMOS technology

CMOS realization of two-dimensional mixed analog-digital Hamming distance discriminator circuits for real-time imaging applications

The architecture of an integrated Hamming artificial neural network, and its use as a versatile signal/image processing circuit is presented. The circuit operation relies oil the charge-based processing of sum-of-products terms, complemented with digital post-processing. The synthesis of complex functions such as winner-(loser)-take-all, k-winner-(loser)-take-all, rank ordering are demonstrated with a minimal hardware overhead. Different operation modes and corresponding hardware configurations are presented. The VLSI realization of the core two-dimensional Hamming distance discriminator, and the chip measurements are discussed. As such, the presented Hamming discriminator is uniquely suitable for real-time image processing and alignment applications. (C) 2008 Elsevier Ltd. All rights reserved

A new method for the in vivo identification of mechanical properties in arteries from cine MRI images: Theoretical framework and validation

Quantifying the stiffness properties of soft tissues is essential for the diagnosis of many cardiovascular diseases such as atherosclerosis. In these pathologies it is widely agreed that the arterial wall stiffness is an indicator of vulnerability. The present paper focuses on the carotid artery and proposes a new inversion methodology for deriving the stiffness properties of the wall from cine-MRI (magnetic resonance imaging) data. We address this problem by setting-up a cost function defined as the distance between the modeled pixel signals and the measured ones. Minimizing this cost function yields the unknown stiffness properties of both the arterial wall and the surrounding tissues. The sensitivity of the identified properties to various sources of uncertainty is studied. Validation of the method is performed on a rubber phantom. The elastic modulus identified using the developed methodology lies within a mean error of 9.6%. It is then applied to two young healthy subjects as a proof of practical feasibility, with identified values of 625 kPa and 587 kPa for one of the carotid of each subject