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This study introduces the use of multiscale amplitude modulation-frequency modulation (AM-FM) texture analysis of multiple sclerosis (MS) using magnetic resonance (MR) images from brain. Clinically, there is interest in identifying potential associations between lesion texture and disease progression, and in relating texture features with relevant clinical indexes, such as the expanded disability...
We present the use of multiscale Amplitude Modulation Frequency Modulation (AM-FM) methods for analyzing brain white matter lesions that are associated with disease progression. We analyze lesions and normal appearing white matter (NAWM) longitudinally (0 and 6 months) and also for progression of disease. We use the expanded disability status scale (EDSS) to assess disease progression. The findings...
In this study the value of magnetic resonance image (MRI) shape and texture analysis was assessed in multiple sclerosis (MS) subjects, both in differentiating between normal or normal appearing and abnormal tissue and in assessing disease onset. Shape and texture analysis was carried out in normal brain white matter and lesions detected in transverse sections of T2-weighted magnetic resonance (MR)...
A problem that occurs in texture analysis and quantitative analysis of magnetic resonance imaging (MRI), is that the extracted results are not comparable between consecutive or repeated scans or, within the same scan, between different anatomic regions. The reason is that there are intra-scan and inter-scan image intensity variations due to the MRI instrumentation. Therefore, image intensity normalization...
Objective: To investigate the differences of texture features among macroscopic lesion white matter (LWM), normal appearing white matter (NAWM) in magnetic resonance images (MRI) from patients with multiple sclerosis (MS) and normal white matter (NWM) from normal controls by gray-level difference statistics, and to detect the hidden abnormality of NAWM. Methods: T2-weighted MRI of 26 MS patients and...
Multiple sclerosis (MS) is a chronic inflammatory disease mainly injuring white matter. Quantitative magnetic resonance imaging (MRI) techniques can improve the detection and quantification of MS. The objective of this study was to observe that whether there is a certain pattern in the changes of texture features in NAWM surrounding the MS lesions. The results corroborate the point. A new method of...
The aim of this study was to investigate the performance of texture analysis in texture classification and tissue discrimination between MS lesions, normal appearing white matter (NAWM) and normal white matter (NWM) in order to support early diagnosis of MS. T2-weighted MR images of sixteen relapsing remitting MS (RRMS) patients and sixteen healthy subjects were selected. Based on the lesion size,...
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...
Reliable segmentation of multiple sclerosis lesions in magnetic resonance brain imaging is important for at least three types of practical applications: pharmaceutical trials, decision making for drug treatment or surgery, and patient follow-up. Manual segmentation of the MS lesions in brain MRI by well qualified experts is usually preferred. However, manual segmentation is hard to reproduce and can...
In this paper, we propose an optimal filter design strategy for the purpose of detecting and segmenting MS lesions in prescribed regions of interest within brain MRI data. Reliable segmentation of multiple sclerosis lesions in magnetic resonance brain imaging is important for at least three types of practical applications: pharmaceutical trials, decision making for drug treatment or surgery, and patient...
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