Ken'ichi Fujimoto

Kagawa University · Faculty of Engineering and Design

As an image reconstruction method for computed tomography, continuous-time nonlinear dynamical systems were proposed. However, as the nonlinear dynamical systems are very large-scale, the numerical analysis is costly and the reconstructed images are not easily obtained. Thus, we apply nonlinear model order reduction algorithm to the nonlinear dynam...

This paper proposes a high-quality computed tomography (CT) image reconstruction method from low-dose X-ray projection data. A state-of-the-art method, proposed by Xu et al., exploits dictionary learning for image patches. This method generates an overcomplete dictionary from patches of standard-dose CT images and reconstructs low-dose CT images by...

Pulsus alternans is a type of arrhythmia that shows alternate contraction forces of ventricular muscles and is a sign of cardiac complications. In this study, we investigate the parameter dependence of pulsus alternans generation using a mathematical crustacean cardiac cell model with automaticity. Specifically, we modified the parameter values in...

Emotion recognition based on EEG signals is one of essential research topics in human-computer interface. Music is regarded as an efficient tool to arouse emotions of human being. This work proposed a scheme that automatically identification the emotions elicited by music. Firstly a music EEG measuring experiment of eight subjects was carried out....

The basic mathematical problem in computed tomography (CT) is defined as finding a nonnegative solution to a rectangular linear system with a sparse coefficient vector and matrix. The coefficient vector and matrix respectively correspond to acquired projection data and a projection operator based on a discrete Radon transform. As an approach to fin...

Canards are interesting nonlinear phenomena that have generated intense research interest since their discovery in the late 20th century. We are interested here in how canard-generating dynamics are influenced by extremely weak periodic perturbations that cause the formation of saddle-node bifurcations in the fundamental harmonic entrainment region...

We present a novel optimization method to handle dose-volume constraints (DVCs) directly in intensity-modulated radiation therapy (IMRT) treatment planning based on the idea of continuous dynamical methods. Most of the conventional methods are constructed for solving inconsistent inverse problems with, e.g., dose-volume based objective functions, a...

This chapter presents a parametric controller to avoid bifurcations of stable periodic points in nonlinear discrete-time dynamical systems. The parameter regulation in the controller can be theoretically derived from the optimization of the maximum local Lyapunov exponent (MLLE) that is closely related to the stability index of stable fixed and per...

We propose a novel controlling methodology for avoiding local bifurcations of stable, hyperbolic fixed and periodic points in nonlinear discrete-time dynamical systems with parameter variation. Dynamical systems may not work as expected owing to bifurcations of desired behavior caused by parameter variation. Controlling parameters to avoid bifurcat...

Diffuse optical tomography (DOT) has potential to provide clinically important functional information which is cannot measured by X-ray CT and MRI. The light is scattered by tissue and an adequate mathematical model is essential for DOT. In this project, we establish the forward model and image reconstruction algorithm based on the radiative transf...

We propose a novel approach for solving box-constrained inverse problems in intensity-modulated radiation therapy (IMRT) treatment planning based on the idea of continuous dynamical methods and split-feasibility algorithms. Our method can compute a feasible solution without the second derivative of an objective function, which is required for gradi...

Bifurcation transitions between a 1D invariant closed curve (ICC), corresponding to a 2D torus in vector fields, and a 2D invariant torus (IT), corresponding to a 3D torus in vector fields, have been the subjects of intensive research in recent years. An existing hypothesis involves the bifurcation boundary between a region generating an ICC and a...

Purpose: The intensity-modulated radiation therapy (IMRT) is an effective therapeutic technique for the treatment of tumors in the human body without inflicting serious damage to normal tissues. IMRT plans include an optimization strategy for minimizing an objective function of radiation beam weights. We present a novel approach for solving non-ne...

For solving inverse problems in computed tomography (CT), we have presented a continuous-time image reconstruction (CIR) system described by a switched nonlinear dynamical system with a piecewise smooth vector field. Recently, we have also proposed an extended CIR (ECIR) system with a modification of the nonlinear vector field, for the purpose of s...

This chapter presents a continuous-time image reconstruction (CIR) system for inverse problems in computed tomography (CT), which generates trajectories by means of solving a set of differential equations. The stability and convergence properties of a non-negatively constrained solution to the linear inverse problem have been theoretically proved,...

Image segmentation is a fundamental technique in image processing. We call the function that extracts blobs (image regions) in a given image and exhibits them in a time series "dynamic image segmentation". It is known that a locally excitatory globally inhibitory oscillator network (LEGION) described by ordinary differential equations is an interes...

Perception of continuous or intermittent sounds ringing in the ears without any external source is referred to as tinnitus. For the management of tinnitus one of the most effective approaches is sound therapy. Previously, we demonstrated a conceptual and computational plastic neural oscillator model for the mechanisms of tinnitus generation and the...

Image segmentation is a key technique in computer aided diagnosis support systems for medical images. We proposed a coupled neuronal system with plastic couplings for segmenting gray-scale images. Proposed system can extract image regions and exhibit them in a time series on the basis of the dynamics of posterization that converts a continuous grad...

In this paper, we analyze the sudden change from chaos to oscillation death generated by the Bonhoeffer-van der Pol (BVP) oscillator under weak periodic perturbation. The parameter values of the BVP oscillator are chosen such that a stable focus and a stable relaxation oscillation coexist if no perturbation is applied. In such a system, complicated...

We have developed a discrete-time dynamical system consisting of a global inhibitor and chaotic neurons that can generate oscillatory responses. We have also found that our system can work as a dynamic image-segmentation system utilizing oscillatory responses of chaotic neurons. Dynamic image segmentation is to severally extract isolated image regi...

Mixed-mode oscillations in a slow-fast dynamical system under weak perturbation are studied numerically. First, we make a band-limited extremely weak Gaussian noise, and apply this noise to this oscillator. Then, we observe random phenomenon from numerical study even if the noise is extremely weak. The mixed-mode oscillations are submerged by chaos...

Many problems with control theory have led to investigations into switched systems. One of the most urgent problems related to the analysis of the dynamics of switched systems is the stability problem. The stability of a switched system can be ensured by a common Lyapunov function for all switching modes under an arbitrary switching law. Finding a...

FPGA Implementation of Discrete-Time Neuronal Network for Dynamic Image Segmentation

An approach for reconstructing tomographic images based on the idea of continuous dynamical methods is presented. The method consists of a continuous-time image reconstruction (CIR) system described by differential equations for solving linear inverse problems. We theoretically demonstrate that the trajectories converge to a least squares solution...

We have developed a discrete-time dynamic image segmentation system consisting of chaotic neurons and a global inhibitor. Our system receives an image with isolated regions and can output segmented images in time series based on oscillatory responses of chaotic neurons. In this article, we derive a reduced model to find intrinsic properties of the...

Many works have been devoted to the study of the behavior of the Bonhoeffer-van der Pol (BVP) oscillator in physiological and biochemical modeling studies. In this paper, bifurcations and chaos in the BVP oscillator, which is intermittently connected to a parallel RC load, are investigated. By using the periodicity of switching action we introduce...

We investigate bifurcations in an iterative method for optimizing an objective function derived from the intensity modulated radiation therapy (IMRT). Through the bifurcation analysis of discrete dynamical systems for small IMRT plans, we obtained bifurcation diagrams showing suitable parameter values for the convergence of fixed points correspondi...

We propose a discrete-time dynamical system of coupled chaotic neurons that can generate oscillatory responses formed by periodic points, and which enables us to develop a dynamic image segmentation system. We calculate bifurcations of periodic points, and investigate a mechanism of the generation of oscillatory responses and parameter regions in w...

Of the iterative image reconstruction algorithms for computed tomography (CT), the power multiplicative algebraic reconstruction technique (PMART) is known to have good properties for speeding convergence and maximizing entropy. We analyze here bifurcations of fixed and periodic points that correspond to reconstructed images observed using PMART wi...

Tinnitus is the perception of phantom sounds in the ears or in the head. Sound therapy techniques for tinnitus treatment have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy from the viewpoint of neural engineering, we have proposed a computational model using a neural oscillator. I...

A dynamic image segmentation system that consists of a chaotic neural network and a global inhibitor has been developed. this is a discrete-time system and is faster than a locally excitatory globally inhibitory network (LEGION) that is a similar system with continuous-time dynamics. it is demonstrated that the system works well and is faster than...

For the recognition of dieren t objects from a natural image, various kinds of methods of range image segmentation have been proposed. In this paper, we treat a scene segmentation method using the LEGION (Locally Excitatory Globally Inhibitory Oscillator Networks), and study dynamical properties of its modied oscillator net- work described by a noi...

Tinnitus is the perception of phantom sounds. There are sound therapy techniques which have the clinical effect of making the sufferers temporarily stop perceiving tinnitus. To account for mechanisms of tinnitus generation and the clinical effect of sound therapy from the viewpoint of neural engineering, this paper describes a neural network model...

Tinnitus is the perception of phantom sounds in the ears or in the head. Sound therapy techniques for tinnitus have been proposed. To account for mechanisms of tinnitus generation and the clinical effects of sound therapies from the viewpoint of neural engineering, we have proposed a plastic neural network model for the human auditory system. We fo...

Tinnitus is a symptom of perceiving phantom sounds. The majority of tinnitus cases are caused by misinterpreting null sounds from ears as significant nervous signals in the cerebral limbic system. There are two typical sound therapies for tinnitus: Tinnitus Masking (TM) and Tinnitus Retraining Therapy (TRT). Their effects have been discussed from c...

Tinnitus is the perception of phantom sounds in the ears or in the head. Accordingly sound therapy for tinnitus has been used. To account for mechanisms of tinnitus generation and the clinical effects of sound therapies from the viewpoint of neural engineering, we have proposed a plastic neural network model for the human auditory system. We found...

Tinnitus is a symptom of perceiving phantom sounds. As one of its treatment techniques, tinnitus retraining therapy (TRT) has been proposed. It consists of psychotherapy by counseling and physical therapy based on masking theory by external stimuli. Our interest is to explain medical effects of the physical therapy from the viewpoint of engineering...

A living body has a mechanism to acquire various periodic signals in the environment. In our nerve system, this is realized by using of simple neural oscillators. The oscillators optimize their internal parameters to synchronize with the external signal only from error between their own output and external signal. Furthermore, a single neural oscil...

A living body has self-organized information processing systems in their nerve system. They construct various internal models of the environment autonomically. Periodic behaviors, such as circadian rhythm, locomotion of limbs in walking and tapping, come from these internal pattern generators. They obtain the periodic signal by use of external stim...

The living body has various biological rhythms with different periods. The nervous system is very important as a mechanism and a control for rhythm generation. However, the detailed constitution and the operating algorithm for the system are not well known for neural physiology or anatomy. We thus propose a hierarchical neural network for generatin...