Optimal focus evaluated using Monte Carlo simulation in non-invasive neuroimaging in the second near-infrared window

Iida, Tatsuto; Yamato, Hiro; Nomura, Yoshihiko

doi:10.1016/j.mex.2019.09.010

Cited by 2 publications

(3 citation statements)

References 14 publications

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“…Digital anatomical data in which the internal structure of the breast was reflected were pursued for the improvement of our previous Monte Carlo model [ 11 , 14 , 15 , 16 ]. In the previous studies, Li et al used a dataset of cross-sectional cryosection images which was provided by the Visible Chinese Human (VCH) [ 12 , 13 ].…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, since the fluence yielded a response to a light source 1 W/cm 2 , it was converted into the response to 50 mW/cm 2 of light source, generally used in tissue spectroscopy [ 13 , 27 ]. The fluence was inherited by the emission photon in two ways as shown in Figure 3 D. In the previous study, without the excitation gradient [ 14 ], the weight of the emission photon was set as spatially constant by the use of excitation fluency in the center of the cancer. In the present study with an excitation gradient, the emission photon had an initial weight dependent on excitation fluency in each voxel.…”

Section: Methodsmentioning

confidence: 99%

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Monte Carlo Modeling of Shortwave-Infrared Fluorescence Photon Migration in Voxelized Media for the Detection of Breast Cancer

et al. 2020

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Recent progress regarding shortwave-infrared (SWIR) molecular imaging technology has inspired another modality of noninvasive diagnosis for early breast cancer detection in which previous mammography or sonography would be compensated. Although a SWIR fluorescence image of a small breast cancer of several millimeters was obtained from experiments with small animals, detailed numerical analyses before clinical application were required, since various parameters such as size as well as body hair differed between humans and small experimental animals. In this study, the feasibility of SWIR was compared against visible (VIS) and near-infrared (NIR) region, using the Monte Carlo simulation in voxelized media. In this model, due to the implementation of the excitation gradient, fluorescence is based on rational mechanisms, whereas fluorescence within breast cancer is spatially proportional to excitation intensity. The fluence map of SWIR simulation with excitation gradient indicated signals near the upper surface of the cancer, and stronger than those of the NIR. Furthermore, there was a dependency on the fluence signal distribution on the contour of the breast tissue, as well as the internal structure, due to the implementation of digital anatomical data for the Visible Human Project. The fluorescence signal was observed to become weaker in all regions including the VIS, the NIR, and the SWIR region, when fluorescence-labeled cancer either became smaller or was embedded in a deeper area. However, fluorescence in SWIR alone from a cancer of 4 mm diameter was judged to be detectable at a depth of 1.4 cm.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Monte Carlo Modeling of Shortwave-Infrared Fluorescence Photon Migration in Voxelized Media for the Detection of Breast Cancer

et al. 2020

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“…In the control module, based on the image estimation, a stepper motor was used to adjust the position of the primary mirror of the telescope in the control device. In Figure 1, the auto-focus process is given as follows [23,24]: firstly, the CCD camera captures information of tracked objects through the telescope and sends the image to the PC control program. Next, the PC control program performs an estimation of the CCD image and sends commands to rotate the stepper motor in a clockwise or counter-clockwise direction.…”

Section: Auto-focus Experiments Setmentioning

confidence: 99%

Accurate and Rapid Auto-Focus Methods Based on Image Quality Assessment for Telescope Observation

Yang

Chen

Zhou³

et al. 2020

Applied Sciences

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Aiming at improving the speed and accuracy of auto-focus for telescope observation, algorithms for image estimation and auto-focus were investigated and are discussed in this article. Based on the image quality assessment, the auto-focusing process of the telescope system is realized by using the mountain-climb search method. Several evaluation functions were tested in different scenarios. It is demonstrated that the Tenengrad image estimation function (IEF) is suitable for an instant and accurate auto-focus process of the telescope. Furthermore, we implemented sampling and dynamic adaptive focusing window (ES-DAFW) methods with the Tenengrad IEF to enhance the sensitivity and accuracy of the auto-focus process. The experimental results showed that our ES-DATW method can provide more accurate results in less time for the auto-focus process compared to the conventional approaches, especially for a sparse image. These results promise significant applications to the auto-focusing of other telescopes with image quality assessment.

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Optimal focus evaluated using Monte Carlo simulation in non-invasive neuroimaging in the second near-infrared window

Abstract: Graphical abstract

Cited by 2 publications

References 14 publications

Monte Carlo Modeling of Shortwave-Infrared Fluorescence Photon Migration in Voxelized Media for the Detection of Breast Cancer

Monte Carlo Modeling of Shortwave-Infrared Fluorescence Photon Migration in Voxelized Media for the Detection of Breast Cancer

Accurate and Rapid Auto-Focus Methods Based on Image Quality Assessment for Telescope Observation

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