基于SVD分解的胆固醇病变检测方法

Sana Lafi, A. Khalfallah, M. Bouhlel
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引用次数: 2

摘要

基于免疫荧光的荧光光谱是医学诊断和筛查不同病理的有用工具,如乳腺癌、动脉粥样硬化……这种诊断通常通过荧光标记来实现,通常被主要与一些自然自动荧光的细胞相关的寄生虫信号所掩盖。本文提出了一种基于奇异值分解的计算方法,用于分析标记动脉发出的荧光信号的主要成分。本分析的目的是提取与荧光源相关的纯光谱及其相对重分配,以便检测和定位胆固醇病变。计算机仿真表明了该方法在处理标记动脉中重叠源问题方面的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A cholesterol lesion detection approach based on SVD decomposition
Fluorescence spectroscopy based on immuno-fluorescence is a useful tool in medical diagnosis and screening for different pathologies, as breast cancer, atherosclerosis … Such a diagnosis, often achieved through a fluorescent labeling, is often obscured by a parasite signal associated mainly with some cells which are naturally auto-fluorescent. This paper proposes a computational method based on Singular Value decomposition which helps analyze the main components of an emitted fluorescent signal by a labeled artery. The aim of this analysis is to extract the pure spectra associated with the fluorescent sources and their relative repartition in order to detect and localize the cholesterol lesion. Computer simulations are presented to illustrate the efficiency of the proposed method in dealing with overlapped source problem in a labeled artery.
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