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Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction

机译:使用NIRFAST的近红外光学层析成像:数值模型和图像重建算法

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Diffuse optical tomography, also known as near infrared tomography, has been under investigation, for non-invasive functional imaging of tissue, specifically for the detection and characterization of breast cancer or other soft tissue lesions. Much work has been carried out for accurate modeling and image reconstruction from clinical data. NIRFAST, a modeling and image reconstruction package has been developed, which is capable of single wavelength and multi-wavelength optical or functional imaging from measured data. The theory behind the modeling techniques as well as the image reconstruction algorithms is presented here, and 2D and 3D examples are presented to demonstrate its capabilities. The results show that 3D modeling can be combined with measured data from multiple wavelengths to reconstruct chromophore concentrations within the tissue. Additionally it is possible to recover scattering spectra, resulting from the dominant Mie-type scatter present in tissue. Overall, this paper gives a comprehensive over view of the modeling techniques used in diffuse optical tomographic imaging, in the context of NIRFAST software package.
机译:漫射光学层析成像技术(也称为近红外层析成像技术)已在研究中,用于组织的非侵入性功能成像,特别是用于乳腺癌或其他软组织病变的检测和表征。为了从临床数据进行精确建模和图像重建,已经进行了许多工作。 NIRFAST是一种建模和图像重建软件包,已开发出来,它能够从测量数据中进行单波长和多波长光学或功能成像。此处介绍了建模技术背后的理论以及图像重建算法,并提供了2D和3D示例以演示其功能。结果表明,可以将3D建模与来自多个波长的测量数据结合起来,以重建组织内的生色团浓度。另外,有可能恢复由组织中存在的主要Mie型散射引起的散射光谱。总体而言,本文在NIRFAST软件包的背景下,全面介绍了用于漫射光学层析成像的建模技术。

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