ANALYSIS OF OPTICAL FIBER SPECKLE PATTERNS FOR DETECTION OF IVUS CATHETER TIP IN 3D SPACE: AN INTELLIGENT SENSOR RESEARCH

1 online resource (105 pages) : PDF

2020

University of North Carolina at Charlotte

This research study presents the architectural design and computational framework for an intelligent tracking sensor constructed from a multimode fiber optic. As laser light travels through an inhomogeneous medium, such as multimode fiber, the random interactions between light rays generate a circular output pattern commonly referred to as speckle patterns. Speckle patterns are highly responsive to the variation in the physical status of a multimode fiber. As a multimode fiber deforms, analysis of speckle pattern variations provides information about the external perturbations causing the deformation. This study presents a novel algorithm for calculating 3D transformations from a series of speckle patterns, which is modeled in three tiers.In the first tier, we have performed a series of experiments to demonstrate, in a deforming multimode fiber, the structural variation of speckle patterns contains deterministic information. That also provides a systematic approach for measuring the deformation parameters of a multimode fiber using a convolutional neural network. Second, we have studied the oscillating behavior of multimode fiber as a function of its length to find the relationship between the sensor's heading direction and the deformation of its sensing fiber tip. By utilizing a Long Short-Term Memory model, we have demonstrated that long-term dependencies between the deformation parameters provide a stable and reliable indication of the intelligent sensor's direction. In the end, we have utilized these findings to develop a novel computational framework for the intelligent sensor. This computational framework includes a pipeline of deep learning models to extract features from a sequence of speckle patterns, and a motion model to estimate the trajectory of the sensor from the extracted features.

doctoral dissertations

Optics
Computer science
Biomedical engineering

Ph.D.

Intelligent Sensor
Machine Learning
Multimode Fiber
Optical Fiber Specklegram Sensor
Speckle Pattern
Specklegram

Computer Science

MOSTAFAVI, M. TAGHI

Saule, Erik
Sayeh, Mohammad
Wartell, Zachary
Hasan, Mohamed-Ali

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2020.

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Razmyar_uncc_0694D_12472

http://hdl.handle.net/20.500.13093/etd:2557