Award Date
May 2023
Degree Type
Thesis
Degree Name
Master of Science in Engineering (MSE)
Department
Electrical and Computer Engineering
First Committee Member
Brendan Morris
Second Committee Member
Sarah Harris
Third Committee Member
Shengjie Zhai
Fourth Committee Member
Mingon Kang
Number of Pages
76
Abstract
In cooperation with the UNLV School of Medicine, this thesis is part of a bigger project aimed at developing a post-op surgery device for the constant unattended monitoring of a patient’s tissue. This device is intended to monitor areas of surgical sites and detect any complications without the need for continuous supervision by medical professionals. One such complication includes inadequate tissue perfusion, or a lack of blood flow reaching a patient’s tissue. The role of this thesis is to fit a convolutional neural network model to the available data gathered from voluntary participants and attempt to classify the data as a different stage of tissue perfusion in the hand area. The device is equipped with a camera setup using three sensing modalities, RGB, thermal infrared, and laser speckle contrast imaging, revealing information that a single conventional camera could not. Once the data is prepared for model training, various techniques will be explored due to the multiple sensing modalities involved in data collection. The techniques range from the training of a single image modality to the topic of data fusion, a key component of the thesis. In the early fusion implementation, the data to be fused is the image channels coming from the 3 modalities, creating a 4 to 5 channel image. The late fusion implementation will train each modality separately, and fuse feature vectors at the end of the model. This thesis will present the implementation and results of both techniques.
Disciplines
Engineering
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Soto, Ivan, "Monitoring and Classification of Tissue Perfusion Through the Combined Use of Thermal, RGB, and Laser Speckle Contrast Imaging" (2023). UNLV Theses, Dissertations, Professional Papers, and Capstones. 4783.
https://digitalscholarship.unlv.edu/thesesdissertations/4783
Rights
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