The aim of this thesis was to develop a software pipeline for tissue analysis in IVOCT by systematically addressing different open questions for analysis. In Chapter 2, we report on a first attempt... Show moreThe aim of this thesis was to develop a software pipeline for tissue analysis in IVOCT by systematically addressing different open questions for analysis. In Chapter 2, we report on a first attempt to quantify the correlation between the position of the catheter with respect to the luminal wall and the image intensities. We implemented the Depth-Resolved (DR) model for IVOCT images in Chapter 3. In addition to the attenuation coefficient, we further extended the model to estimate a backscatter term, and proposed an algorithm to exclude the noisy region. For the first time, it was implemented in IVOCT images with fast and robust calculations. Results show that the IVOCT intensity, DR attenuation coefficient and backscatter term extracted with the reported implementation are complementary to each other in characterizing six tissue types. In Chapter 4, we applied an exact histogram specification technique to covert data generated using different vendors e.g. 8-bit Terumo data and 16-bit St. Jude data. For the application of the DR algorithm, the optical parameters were analyzed as features for the maturity of post-stenting neointima in Chapter 5. In Chapter 6, the three values were analyzed for the determination of thrombi types with high reproducibility. Show less
As mentioned above, IVOCT, as a novel imaging modality, has played an active role in a wide range of CAD applications, including research and clinical routine. Due to its unparalleled high... Show moreAs mentioned above, IVOCT, as a novel imaging modality, has played an active role in a wide range of CAD applications, including research and clinical routine. Due to its unparalleled high resolution and the ability to delineate complex vascular structures, IVOCT technology makes many precise measurement and novel applications possible. However, currently, a lot of analyses in IVOCT images are still relying on the manual work which decreases their value. The goal of this thesis is to develop robust and accurate (semi)automated methods that can detect and segment the interesting components in IVOCT pullback runs, such as implanted stent struts and side branches in 3D for accurate measurement, so that the results could contribute to medical research as well as for clinical decision-making. My thesis presents four different automated algorithms to detect metallic stent struts, bioresorbable vascular scaffold struts, side branches and all the common components in IVOCT images. It also presented a semi-automated method to assess the stent support to vessel wall and the stent-jailed side branch access through stent cells in 3-dimentional space Show less
