Though molecular and cellular level modeling is the first step in the long of for clinical ladder multiscale modeling translational application, it may be regarded as the critical scale: "Where the rubber meets the road." The idiom from automotive engineering refers to the critical endpoint where all the ancillary engineering fuel system, chassis, pistons, etc. is finally tested. In the realm o...

W E are very pleased to introduce this Special Issue of TBME LETTERS on Multiscale Modeling and Analysis in Computational Biology and Medicine. We received an overwhelming response of our Call for Papers for this Special Issue with 243 manuscripts. Considering the significance of research interests in this area of high potential impact, and the large number of worthy manuscripts, we decided to ...

In this paper, a new wavelet-packet multiscale image segmentation method is presented first. By combining this new method with a multiscale region-based segmentation method, we develop a new generic systematic scheme to segment targets in images based on multiscale analysis in both grayscale and space. Based on the new scheme, a system framework is constructed to intelligently segment targets a...

This paper discusses the multiscale method for the time-dependent Maxwell’s equations with memory effects in composite materials. The main difficulty is that one cannot use the usual multiscale asymptotic method (cf. [25, 4]) to solve this problem, due to the complication of the memory terms. The key steps addressed in this paper are to transfer the original integrodifferential equations to the...

Abstract. A fully discrete a priori analysis of the finite element heterogenenous multiscale method (FE-HMM) introduced in [A. Abdulle, M. Grote, C. Stohrer, Multiscale Model. Simul. 2014] for the wave equation with highly oscillatory coefficients over long time is presented. A sharp a priori convergence rate for the numerical method is derived for long time intervals. The effective model over ...

Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB-NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation that ...

Discrete energy minimization is a ubiquitous task in computer vision, yet is NP-hard in most cases. In this work we propose a multiscale framework for coping with the NP-hardness of discrete optimization. Our approach utilizes algebraic multiscale principles to efficiently explore the discrete solution space, yielding improved results on challenging, non-submodular energies for which current me...

For regularly spaced one-dimensional data, wavelet shrinkage has proven to be a compelling method for non-parametric function estimation. We create three new multiscale methods that provide wavelet-like transforms both for data arising on graphs and for irregularly spaced spatial data in more than one dimension. The concept of scale still exists within these transforms, but as a continuous quan...

The analysis to detect arrhythmias and life-threatening conditions are highly essential in today world and this analysis can be accomplished by advanced non-linear processing methods for accurate analysis of the complex signals of heartbeat dynamics. In this perspective, recent developments in the field of multiscale information content have lead to the Microcanonical Multiscale Formalism (MMF)...

We propose a multiscale method based on a finite element heterogeneous multiscale method (in space) and the implicit Euler integrator (in time) to solve nonlinear monotone parabolic problems with multiple scales due to spatial heterogeneities varying rapidly at a microscopic scale. The multiscale method approximates the homogenized solution at computational cost independent of the small scale b...