Feng Jinchao, Jiang Shudong, Pogue Brian W, Paulsen Keith
Beijing Key Laboratory of Computational Intelligence and Intelligent System, Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
Thayer School of Engineering, Dartmouth College, NH 03755, USA.
Biomed Opt Express. 2018 Jun 25;9(7):3266-3283. doi: 10.1364/BOE.9.003266. eCollection 2018 Jul 1.
Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast by 10%, the contrast to noise ratio by 20% and the full width half maximum (FWHM) by 30%. The results from phantoms and human images show that a linear inverse distance weighting function appears optimal, and that incorporation of this function can generally improve the recovered total hemoglobin contrast of the tumor to the normal surrounding tissue by more than 15% in human cases.
结构图像引导近红外光谱断层扫描（NIRST）已被开发出来，作为一种在图像引导的组织光谱特征量化背景下使用漫反射近红外光谱的方法。一种用于NIRST的直接正则化成像（DRI）方法具有无需任何图像分割的优点。在此，我们开展了一项全面的研究，以分析在基于DRI的NIRST中对光学系数恢复进行加权时所隐含的加权函数的影响。这是通过模拟、体模和临床患者检查数据来完成的。已知真实物体的模拟表明，该加权函数的变化可使对比度变化10%，对比度噪声比变化20%，半高宽（FWHM）变化30%。体模和人体图像的结果表明，线性反比距离加权函数似乎是最优的，并且在人体病例中，纳入该函数通常可使肿瘤与周围正常组织的总血红蛋白恢复对比度提高超过15%。
