Skeletal muscle fascia is a connective tissue which provides structure and aidswith force transfer in a muscle. Currently there are no good ways of detectingand analyzing micrometer thick structures of this tissue in-vivo. In this thesis,we created a model to detect skeletal muscle fascia, and tested its performanceusing simulated data. Utilizing the ultrasound simulation software Vantage,which operates through MATLAB, we created a simulation model which repli-cates the properties and behaviour of skeletal muscle fascia. To detect thetissue, we changed and adapted a previously implemented model of ultrasoundlocalization microscopy (ULM), previously only used to create super resolutionimages of blood vessels. Finally we evaluated the models ability to locate anddetermine the thickness of the simulated fascia. Additionally we tested themodels ability to separate adjacent objects.We found that our model was successful at detecting and localizing thesimulated fascia, with a sub wavelength accuracy. The precision of the locatedfascia appears more accurate for horizontally aligned objects compared to thevertically aligned ones. The results from determining the thickness of the fasciaproved relatively successful as well. However the results showed a high variance.This could be improved through an inclusion of stocasticity in the simulationmodel we developed. Finally the ability to distinguish two objects close to eachother showed successful results as well. The method was able to clearly detecta fascia circle with a 0.5mm diameter. It was unable to detect the sides a fasciacircle with a 0.25mm diameter.The main limitation with the model we have developed lies in the simulationsperformed. The simulation model we used was very basic, meaning that it didnot perfectly represent the skeletal muscle fascia we sought to examine. Furtherdevelopment of the simulation model is required to provide a result which ismore representative of real skeletal muscle fascia.The analysis of this first model shows promise in detecting the simplifiedfascia provided by our simulation model. At this stage, the method will requiremore extensive testing, together with a more thorough statistical analysis, beforewe can state the usefulness of the method.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-199579 |
| Date | January 2022 |
| Creators | Behndig, Oscar |
| Publisher | Umeå universitet, Institutionen för fysik |
| 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 |
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