کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7224035 | 1470565 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Time Resolved Diffuse Optical Tomography model
ترجمه فارسی عنوان
مدل توموگرافی نوری توزیع شده با زمان حل شده
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی (عمومی)
چکیده انگلیسی
Time Resolved Diffuse Optical Tomography (TRDOT) modality is presented. Images were reconstructed for four different scenarios. 64-source and 64-detector bifurcated positions were used for simulation model. Inclusion was buried in different coordinate locations. Time-dependent diffusion equation for photon-tissue interactions were used to create the forward model. Mostly used TRDOT devices have pulsed-laser source and photo-multiplier tube (PMT) photodetectors. In addition to pulsed laser source, continuous wave (CW) sources would be used for TRDOT imaging. In general usage, solid-state diode pumped pulsed-lasers and driving units constitute source module. Solid-state lasers are made of Titanium Sapphire (TiSa). These laser sources are difficult to use, modify, maintain, and they are also expensive. Instead of using expensive pulsed laser sources, cheap electronic-based pulsed-laser driving circuit will be implemented. Pseudomorphic high electron mobility transistors (pHEMTs) as switching elements will be used at both pulsed-laser and photodiode current readout sides. Hence, this work is taking its motivation from the next-generation electronic-based device instrument, creating the time dependent forward model as its focus. In this work, it was seen that selection of time intervals are important parameters to reconstruct the hidden images inside the homogeneous tissue. Inclusion was buried inside the homogeneous tissue model, and corresponding time modes have been selected to extract the hidden inclusion. In this work, time modes were analyzed for the TRDOT device. It has been realized that different time mode forward model weight functions should be used for different depth layers to reconstruct the hidden inclusion correctly. Hence, different time mode forward model weight matrix functions were generated from time 20â¯ps to 400â¯ps by 20â¯ps steps, and from time 2â¯ps to 40â¯ps by 2â¯ps steps. In the mathematical inverse problem solution algorithm, these time clusters were used to create two different weight matrixes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Optik - Volume 162, June 2018, Pages 133-139
Journal: Optik - Volume 162, June 2018, Pages 133-139
نویسندگان
Huseyin Ozgur Kazanci,