eLearning

Extraction of multiple sclerosis lesions in MR images based on active contours

Elif Işıkçı; Dilek Göksel Duru 2015 Medical Technologies National Conference (TIPTEKNO), 2015

In this study, a semi automatic segmentation of multiple sclerosis lesions in magnetic resonance (MR) images based on active contours is done. Based on the seed area selection by the user, the parametric active contours which rely on energy minimization, try to shrink and bend the snake resulting in boundary curve (capture region). The method is tested in MATLAB firstly ...

Detection of hyperintense regions on MR brain images using a Mamdani type Fuzzy Rule-Based System: Application to the detection of small multiple sclerosis lesions

F. X. Aymerich; P. Sobrevilla; E. Montseny; A. Rovira 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 2011

In this paper we present an algorithm for detecting hyperintense regions in brain images acquired by Magnetic Resonance Imaging. The work is part of a more general research oriented to the design of support tools that assist the healthcare experts in their research activities on brain diseases. The algorithm has been focused on the detection of small multiple sclerosis lesions ...

Automated corpus callosum extraction via Laplace-Beltrami nodal parcellation and intrinsic geodesic curvature flows on surfaces

Rongjie Lai; Yonggang Shi; Nancy Sicotte; Arthur W. Toga 2011 International Conference on Computer Vision, 2011

Corpus callosum (CC) is an important structure in human brain anatomy. In this work, we propose a fully automated and robust approach to extract corpus callosum from T1-weighted structural MR images. The novelty of our method is composed of two key steps. In the first step, we find an initial guess for the curve representation of CC by using the ...

Non-invasive diagnosis of myopathy using transputer EMG analysis

A. W. Preece; D. L. Preece; R. Jones; J. Green; H. Morgan Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society,, 1989

Surface recorded electromyogram (EMG) interference patterns were analyzed online for turns, zero crossings, frequency content and amplitude data. Patients studied with this technique had multiple sclerosis, dermatomyositis and various dystrophies. The different characteristics illustrated by the measurement technique are shown. It is found that mathematical analysis of EMG signals, even from surface recordings, contains sufficient data to characterize certain myopathies

Texture Characteristic Analysis of MRI for Exploratory Study on Early Diagnosis of Multiple Sclerosis

Lei Wang; Ning Li; Xiaoxia Zhou; Longzheng Tong 2007 IEEE/ICME International Conference on Complex Medical Engineering, 2007

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, which leads to focal plaques of demyelination and axonal impairment in the central nervous system. Multiple sclerosis occurred in brain tissue, optic nerve and spinal cord, mainly in brain tissue, which leads to severe progressive neurological dysfunction, such as blindness, paralysis and death. There are about 65,000 ...

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IEEE-USA E-Books

• Diseases and Injuries of the Central Nervous System Leading to Sensory-Motor Impairment

  Damage to the central and peripheral nervous systems is associated with a loss of motor drive and a defective afferent input to the central nervous system (CNS). This chapter starts with a presentation of neuron injury. The injuries are categorized based on the extent and type of damage to the nerve and the surrounding connective tissue. The chapter addresses sensory - motor deficits that are caused by neuron injury or disease: (a) cerebrovascular accident (CVA), or stroke, which causes impairments due to changes in blood supply to the brain; (b) spinal cord injuries (SCIs), which result in total or partial obstruction of flow of both sensory and motor information between the peripheral and central nervous systems; (c) nontraumatic disorders of the CNS (amyotrophic lateral sclerosis and multiple sclerosis); and (d) cerebral palsy (CP). Finally, the chapter presents the incidence of CNS diseases.

• Propagation of the Action Potential

  There are two types of regenerating nerve fibers: unmyelinated and myelinated. Unmyelinated fibers are generally small (diameter up to 0.0013 mm or 0.00005 in.) and have a slow speed [up to 1.5 meters/second (m/s) or 3.2 mph]. Two- thirds of the fibers in the body are of this type; they are used for chores for which low speed is adequate, such as the reporting of pain and temperature. A regenerating axon fires (starts to generate an action potential [AP]) when the voltage across the membrane rises above a threshold level such as 8 mV. The AP propagates like an ocean wave; the conduction speed of an unmyelinated fiber is determined by the forward speed of the wavefront at the 8-mV level. Myelinated fibers are relatively large (diameter up to 0.022 mm or 0.0009 in.) and have a high speed (up to 130 m/s or 290 miles per hour [mph]). They are used for the retrieval and processing of information where high speed is vital. A myelinated fiber is high speed because its membrane is relatively thick, but it is interrupted by nodes at which the AP is regenerated. The conduction speed is determined by the time taken for the AP to reach the 8-mV level from one node to the next. This time is approximately constant, 17 µs, regardless of nerve fiber diameter. Nonregenerative or weakly regenerative sections of nerve fiber are reflected in lower-than-normal conduction speeds; this is important clinical evidence for nerve dysfunction, such as in multiple sclerosis.

• Robot-Assisted Neurorehabilitation

  This chapter addresses the use of robots to facilitate the recovery of neuromotor functions. Early approaches to robot-based therapy were mostly empirical and limited by the available hardware, designed for industrial applications. More recent applications build on the current understanding of the physiology of the reorganization of the nervous system following a lesion. The chapter focuses on rehabilitation of the upper limb, but similar principles are applicable to the lower limb. It addresses the neuromotor recovery of chronic stroke survivors and examines two case studies in more detail. Then, the chapter discusses the available evidence on the efficacy of robot therapy. Finally, it suggests that robots may be potentially useful in the context of other neurological diseases, for example, multiple sclerosis and cerebral palsy.