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https://hdl.handle.net/10356/142766
Title: | Carotid artery stenosis (CAS) disease detection by passive and active medical infrared (IR) thermal imaging | Authors: | Saxena, Ashish | Keywords: | Engineering::Mechanical engineering::Fluid mechanics Science::Medicine::Computer applications |
Issue Date: | 2020 | Publisher: | Nanyang Technological University | Source: | Saxena, A. (2020). Carotid artery stenosis (CAS) disease detection by passive and active medical infrared (IR) thermal imaging. Doctoral thesis, Nanyang Technological University, Singapore. | Abstract: | Carotid artery stenosis (CAS) or atherosclerosis, wherein narrowing of the carotid artery passage occurs as a result of endothelial cell dysfunction and inflammation that leads to thrombosis formation. With the presence of stenosis, alterations in the carotid artery hemodynamics bring about changes in the heat transfer to the surrounding tissue, which is expected to translate into resulting temperature maps over the external skin surface; possibly correlates to the presence of stenosis. These abnormal temperature maps could be captured and quantified using non-contact/non-invasive infrared (IR) thermal imaging/thermography. Labeled with Duplex Ultrasound examination, a total of 134 carotid arteries samples from 67 study participants were studied using both passive (80 samples from 40 participants) and active (with external cooling stimulation, 54 samples from 27 participants) thermographic techniques, which resulted in an accuracy of 94% and 85%, respectively. This study suggests the potential of thermography as a possible screening tool for CAS patients. | URI: | https://hdl.handle.net/10356/142766 | DOI: | 10.32657/10356/142766 | Schools: | School of Mechanical and Aerospace Engineering | Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | MAE Theses |
Files in This Item:
File | Description | Size | Format | |
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Thesis_Revised Version-Ashish Saxena.pdf | Thesis | 6.96 MB | Adobe PDF | ![]() View/Open |
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