Time-domain diffuse optical tomography (TD-DOT) is interested to many scholars due to its unique features such as rich information in each measured pulse, elimination of cross-talk in the reconstruction, and no need for the measurement calibration, although TD-DOT imaging system requires very expensive equipment. Usually, the generalized pulse spectrum technique (GPST) is applied to transform the real domain optical diffusion forward model into its Laplacian domain. However, the application of TD-DOT has been limited by the low spatial resolution due to strong optical scattering in tissues. In this study, we introduced the anatomical guidance from computed tomography (CT) and positron emission tomography (PET) into TD-DOT to improve the quality of the reconstructed TD-DOT images with the soft prior method. Furthermore, we have investigated to maximize the utilization of the rich information contained in the measured pulses by increasing the frequency number in the Laplacian transformation. To validate the proposed method, we have performed numerical simulation studies by using the CT/PET breast images of a breast cancer patient, in which we generated the breast mesh from CT images and obtained the breast tumor position and size from the PET images. The soft prior guidance based TD-DOT reconstruction was performed in the Laplacian domain. Our simulation results indicate that the spatial resolution and the accuracy of the reconstructed TD-DOT images have been improved substantially after applying the anatomical guidance.
In order to investigate the variation of indoor carbon dioxide concentration and how it changes with human activities, a tunable diode laser absorption spectroscopy (TDLAS) system was used to monitor the indoor CO2 concentration. Based on Wavelength Modulation Spectroscopy double frequency detection (WMS-2f), the 2v1+v3 characteristic line (4991.26 cm-1) of CO2 was measured by a DFB laser. The measured concentration values were calibrated by means of a cell filled with reference gas. The results show that the daily average indoor CO2 concentrations is about 419ppm which is slightly higher than that of the outdoor and the changing range is between 380ppm and 510ppm in a day. The indoor CO2 concentration was influenced by the change of ventilation and indoor staff. The respiration of the indoor staff makes a greater impact on a relatively confined indoor CO2 concentration. The CO2 increasing rate is measured to be 80ppm/hour in the case of occupant density of 0.06 people/m3. Therefore, the staff crowded indoor should ventilate timely to prevent excessive CO2 causing people discomfort.
Time-domain optical mammography has attracted many attentions since it can diagnose early breast cancer by efficiently
reconstructing optical parameter. However, the currently available image reconstruction algorithms for time-domain
optical mammography are badly influenced by different Jacobian magnitudes of absorption coefficient and reduced
scattering coefficient. To improve image quality, we proposed an efficient Jacobian scaling method with a relative data
type based on generalized pulse spectrum technique. Our simulated and experimental reconstructions show that this
Jacobian scaling method can efficiently enhancing the quality of reconstructed image.
Breast diffuse optical tomography is now highly expected as a potential routine inspection means for the high specificity
and safety. Many efforts have been put to overcome its intrinsic adversities, such as low spatial resolution and
quantitativeness. In this study, we propose a technique for enhancing image reconstruction of time-domain breast diffuse
optical tomography (DOT). The technique uses finite-element-method (FEM) solution to the Laplace-transformed
diffusion equation as the forward model, and an inverse model of Newton-Raphson iterative scheme. Through a target
location that is provided by the preliminary image that is reconstructed using global optode arrangement or other
techniques, we can obtain a more accurate image reconstruction by relocating all the optodes within the targeted region.
The simulative experiments show that the performance of reconstructed image is evidently improved by the aid of the
optodes relocation strategy.
The investigations on the optical mammography have attracted many clinical attentions, since the conventional X-ray mammography has shown some deficiencies in sensitivity, specificity, security and comfortableness. In this study, we propose an image reconstruction technique of time-domain diffuse optical tomography (DOT) for the optical mammography in the first place. This technique uses the finite-element method (FEM) solution to the Laplace-transformed coupled diffusion equations as the forward model, and develops an inverse model based on a Newton-Raphson scheme. On the basis of the preliminary reconstructed image of this technique, we also present an efficient Jacobian reduction method by the aid of image segmentation to obtain a more accurate image reconstruction. The simulative experiments reveal that the performance of reconstructed image by the aid of the image segmentation makes a notable improvement on the conventional algorithm in breast phantom image.
We present our preliminary results on two-dimensional (2-D) optical tomographic imaging of hemodynamic changes of two preterm infant brains in different ventilation settings conditions. The investigations use the established two-wavelength, 16-channel time-correlated single photon counting system for the detection, and the generalized pulse spectrum technique based algorithm for the image reconstruction. The experiments demonstrate that two-dimensional diffuse optical tomography may be a potent and relatively simple way of investigating the functions and neural development of infant brains in the perinatal period.
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