Microcirculation plays an essential and functional role in the human body and reflects people’s physical status with microscopic detail. For peripheral microcirculation, nail-fold microscopy is a convenient and non-invasive tool since the capillaries in the nail-fold are well arranged and parallel to the skin, which is advantageous for microscopic visualization. Further, nail-fold capillaroscopy information is widely useful. In diagnosis, various diseases such as systemic lupus erythematosus and cardiac diseases can be detected and predicted at an early stage with capillaroscopic patterns and capillary blood velocity. For medical experiments, capillaroscopic information can be used to monitor drug effects and other medical treatments. Though nail-fold capillaroscopy is of significant convenience, it is not widely used. Currently, there is no commercial product with those functions due to the limitations of the equipment, such as microscope resolution and lens magnification. Besides, there is no concrete standard for measurement procedures or objective rules for quantitive data analysis. This thesis proposes a reliable system estimating nail-fold capillary blood flow velocity. It is tested and applied to the microscope from Optilia. In this work, various image and video processing methods are discussed in detail and tested in practice. Taking computational load and equipment limitations into consideration, the system applies frame enhancement and video stabilization. It uses dual-window and correlation methods to estimate the velocity of red blood cells in nail-fold capillaries. In order to test the reliability of the system, the obtained results are compared with the outcome of direct observation. It turns out that the chosen methods employed in the system provide rational results within 5 pixel bias.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-174869 |
| Date | January 2015 |
| Creators | Wang, Chen |
| Publisher | KTH, Skolan för elektro- och systemteknik (EES) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | TRITA-EE, 1653-5146 ; 2015:59 |
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