Time of Flight Diffraction (TOFD) is one of the most accurate ultrasonic methods for crack detection and sizing in pipeline girth welds. Its performance, however, is limited by the temporal resolution of the signal. In this thesis, we develop a signal processing method based on autoregressive spectral extrapolation to improve the temporal resolution of ultrasonic signals. The original method cannot be used in industrial applications since its performance is highly dependent on selection of a number of free parameters. This method is modified by optimizing its various steps and limiting the number of free parameters, and an automated algorithm for selection of values for the remaining free parameters is proposed based on the analysis of a large set of synthetic signals. The performance of the final algorithm is evaluated using experimental data; it is shown that the uncertainty in crack sizing accuracy can be reduced by as much as 80%. Furthermore, the proposed method is shown to be capable of resolving overlapping echoes; therefore, smaller cracks that have echoes that are not clearly resolved in the raw signal, can be detected and sized in the enhanced signal.

This study explored the imaging capability of our frequency-domain photoacoustic (FD-PA) system that utilizes correlation processing alias “photoacoustic radar” and ultrasonic phased array for imaging of soft tissues. The probe imaging capabilities were studied using tissue-mimicking phantoms, tissue samples ex vivo, blood vessels in a human wrist and a rat tumour model in vivo. Our experimental results have shown decent image correlation between our FD-PA and a clinical ultrasound modality. In comparison with ultrasound, we have also demonstrated strong potential of the FD-PA for deep (~15 mm) subsurface imaging with excellent contrast and high signal-to-noise ratio. Additionally, we assessed the potential of silica-coated super paramagnetic iron oxide nanoparticles (SPION) as a novel PA contrast agent. Detection of the nanoparticles up to 24 mm inside an optically tissue-like turbid media and about 5-fold PA signal amplification due to their presence in sheep blood (~1.4 mg/ml) are presented.

Time of Flight Diffraction (TOFD) is one of the most accurate ultrasonic methods for crack detection and sizing in pipeline girth welds. Its performance, however, is limited by the temporal resolution of the signal. In this thesis, we develop a signal processing method based on autoregressive spectral extrapolation to improve the temporal resolution of ultrasonic signals. The original method cannot be used in industrial applications since its performance is highly dependent on selection of a number of free parameters. This method is modified by optimizing its various steps and limiting the number of free parameters, and an automated algorithm for selection of values for the remaining free parameters is proposed based on the analysis of a large set of synthetic signals. The performance of the final algorithm is evaluated using experimental data; it is shown that the uncertainty in crack sizing accuracy can be reduced by as much as 80%. Furthermore, the proposed method is shown to be capable of resolving overlapping echoes; therefore, smaller cracks that have echoes that are not clearly resolved in the raw signal, can be detected and sized in the enhanced signal.

This study explored the imaging capability of our frequency-domain photoacoustic (FD-PA) system that utilizes correlation processing alias “photoacoustic radar” and ultrasonic phased array for imaging of soft tissues. The probe imaging capabilities were studied using tissue-mimicking phantoms, tissue samples ex vivo, blood vessels in a human wrist and a rat tumour model in vivo. Our experimental results have shown decent image correlation between our FD-PA and a clinical ultrasound modality. In comparison with ultrasound, we have also demonstrated strong potential of the FD-PA for deep (~15 mm) subsurface imaging with excellent contrast and high signal-to-noise ratio. Additionally, we assessed the potential of silica-coated super paramagnetic iron oxide nanoparticles (SPION) as a novel PA contrast agent. Detection of the nanoparticles up to 24 mm inside an optically tissue-like turbid media and about 5-fold PA signal amplification due to their presence in sheep blood (~1.4 mg/ml) are presented.

Revascularization of Chronic Total Occlusions (CTO) by percutaneous coronary interventions is limited by low success rates, primarily due to difficulty in guidewire crossing. There are a number of contributing factors that make guidewire crossing challenging. Two of the most significant impediments are: a) inability to adequately visualize the CTO to appropriately plan a pathway to the distal lumen, and b) difficulty in physically crossing the rigid endcap at the proximal end of CTO without using stiff wires. Moreover, there is a significant knowledge gap in the composition of CTOs, and the consequent impact of that composition on crossability. This thesis presents tools and techniques to help mitigate the current shortcomings, while shedding new light on CTO composition and maturation. The tools and techniques presented herein are based upon ultrasound approaches with the intent of eventually developing these strategies into catheter based solutions. Recent studies have suggested that the presence of microvessels in CTO may provide a preferred pathway for guidewire crossing. However, due to limited resolution and a lack of soft tissue contrast in angiography, microvessels within CTO cannot generally be detected by in-vivo angiographic techniques, and when they are visualized, it is unknown whether or not they are intraluminal. In this thesis, high frequency ultrasound with Power Doppler overlays is shown to be capable of detecting and tracking transluminal recanalization channels using an in vivo porcine model of CTO. It is also shown that ultrasound is a more sensitive technique to detect and map these channels than MRI. Furthermore, features of microvasculature in CTOs that had not previously been seen are presented. A technique was then developed to facilitate guidewire crossing through the proximal endcap, also known as the proximal fibrous cap (PFC). In order to assess the ease with which a probe is able to iv perforate the PFC, a system was designed and to measure the force required for PFC puncture. This system was validated by examining the required puncture forces for CTOs of different ages. It was shown that CTOs less than 6 weeks in age are significantly easier to puncture than those greater than 12 weeks. This coincides with differences in composition, with the presence of softer materials at the earlier time point, such as thrombus and proteoglycans compared to stiffer fibrotic materials which predominate at late timepoints. After development and validation of a reliable technique to measure ease of PFC puncture, the efficacy of therapies designed to modify PFC compliance could be assessed. The use of ultrasound mediated microbubble (UMM) disruption to act as an adjuvant to accelerate collagenase therapy in CTO was examined. A significant reduction in puncture force and an increase in the amount of collagen degraded was achieved using a combined UMM + collagenase treatment compared with collagenase therapy alone and UMM treatment alone.

Revascularization of Chronic Total Occlusions (CTO) by percutaneous coronary interventions is limited by low success rates, primarily due to difficulty in guidewire crossing. There are a number of contributing factors that make guidewire crossing challenging. Two of the most significant impediments are: a) inability to adequately visualize the CTO to appropriately plan a pathway to the distal lumen, and b) difficulty in physically crossing the rigid endcap at the proximal end of CTO without using stiff wires. Moreover, there is a significant knowledge gap in the composition of CTOs, and the consequent impact of that composition on crossability. This thesis presents tools and techniques to help mitigate the current shortcomings, while shedding new light on CTO composition and maturation. The tools and techniques presented herein are based upon ultrasound approaches with the intent of eventually developing these strategies into catheter based solutions. Recent studies have suggested that the presence of microvessels in CTO may provide a preferred pathway for guidewire crossing. However, due to limited resolution and a lack of soft tissue contrast in angiography, microvessels within CTO cannot generally be detected by in-vivo angiographic techniques, and when they are visualized, it is unknown whether or not they are intraluminal. In this thesis, high frequency ultrasound with Power Doppler overlays is shown to be capable of detecting and tracking transluminal recanalization channels using an in vivo porcine model of CTO. It is also shown that ultrasound is a more sensitive technique to detect and map these channels than MRI. Furthermore, features of microvasculature in CTOs that had not previously been seen are presented. A technique was then developed to facilitate guidewire crossing through the proximal endcap, also known as the proximal fibrous cap (PFC). In order to assess the ease with which a probe is able to iv perforate the PFC, a system was designed and to measure the force required for PFC puncture. This system was validated by examining the required puncture forces for CTOs of different ages. It was shown that CTOs less than 6 weeks in age are significantly easier to puncture than those greater than 12 weeks. This coincides with differences in composition, with the presence of softer materials at the earlier time point, such as thrombus and proteoglycans compared to stiffer fibrotic materials which predominate at late timepoints. After development and validation of a reliable technique to measure ease of PFC puncture, the efficacy of therapies designed to modify PFC compliance could be assessed. The use of ultrasound mediated microbubble (UMM) disruption to act as an adjuvant to accelerate collagenase therapy in CTO was examined. A significant reduction in puncture force and an increase in the amount of collagen degraded was achieved using a combined UMM + collagenase treatment compared with collagenase therapy alone and UMM treatment alone.

Les malalties cardiovasculars són una de les principals causes de mortalitat als països desenvolupats. La majoria d'elles són degudes a malalties arterials (especialment les coron ries), que vénen causades per l'acumulació de placa. Aquesta patologia estreny el flux sanguini (estenosi) i afecta les propietats elàstiques i bio-mecàniques (arteriosclerosi) de les artèries. En les últimes dècades, l'Ecografia Intra-Coronària (EIC) ha esdevingut una tècnica usual de diagnòstic per la imatge i seguiment de les malalties coronàries. L'EIC està basada en un cateterisme que mostra una seqüència d'imatges corresponents a seccions de l'artèria sota estudi. La inspecció visual de cadascuna d'aquestes imatges proporciona informació sobre el percentatge d'estenosi, mentre que la inspecció de les vistes longitudinals propociona informació sobre les propietats bio-mecàniques, que pot prevenir un desenllaç fatal de la malaltia cardiovascular. Per una banda, la dinàmica arterial (deguda al batec del cor, entre d'altres) és un dels principals artefactes per poder explorar les propietats biomecàniques. Al mateix temps, les mesures manuals d'estenosi requereixen un traçat manual de les vores del vas, tasca feixuga que consumeix molt de temps i que pot patir variabilitat entre observadors.Aquesta tesi proposa vàries eines de processament d'imatge per explorar la dinàmica de les artèries i les seves estructures. Presentem un model físic per extreure, analitzar i corregir la dinàmica rígida transversal dels vasos i per recuperar la fase cardíaca. A més, introduïm un mètode estadístic-determinista per a la detecció automàtica de les vores del vas. En particular, l'enfoquem a segmentar l'adventícia. Un protocol de validació acurat per assegurar una aplicació clínica fiable dels mètodes és un pas crucial en qualsevol proposta d'algorisme. En aquesta tesi tenim especial cura de dissenyar protocols de validació per a cadascuna de les tècniques proposades i contribuïmm a la validació de la dinàmica in vivo amb un indicador objectiu i quantitatiu per mesurar la quantitat de moviment suprimida. / Cardiovascular diseases are a leading cause of death in developed countries. Most of them are caused by arterial (specially coronary) diseases, mainly caused by plaque accumulation. Such pathology narrows blood flow (stenosis) and affects artery bio-mechanical elastic properties (atherosclerosis). In the last decades, IntraVascular UltraSound (IVUS) has become a usual imaging technique for the diagnosis and follow up of arterial diseases. IVUS is a catheter-based imaging technique which shows a sequence of cross sections of the artery under study. Inspection of a single image gives information about the percentage of stenosis. Meanwhile, inspection of longitudinal views provides information about artery bio-mechanical properties, which can prevent a fatal outcome of the cardiovascular disease. On one hand, dynamics of arteries (due to heart pumping among others) is a major artifact for exploring tissue bio-mechanical properties. On the other one, manual stenosis measurements require a manual tracing of vessel borders, which is a time-consuming task and might suffer from inter-observer variations.This PhD thesis proposes several image processing tools for exploring vessel dynamics and structures. We present a physics-based model to extract, analyze and correct vessel in-plane rigid dynamics and to retrieve cardiac phase. Furthermore, we introduce a deterministic-statistical method for automatic vessel borders detection. In particular, we address adventitia layer segmentation. An accurate validation protocol to ensure reliable clinical applicability of the methods is a crucial step in any proposal of an algorithm. In this thesis we take special care in designing a validation protocol for each approach proposed and we contribute to the in vivo dynamics validation with a quantitative and objective score to measure the amount of motion suppressed.

Many clinicians regard speckle noise as an undesirable artifact in ultrasound images masking the underlying pathology within a patient. Speckle noise is a random interference pattern formed by coherent radiation in a medium containing many sub-resolution scatterers. Speckle has a negative impact on ultrasound images as the texture does not reflect the local echogenicity of the underlying scatterers. Studies have shown that the presence of speckle noise can reduce a physician's ability to detect lesions by a factor of eight. Without speckle, small high-contrast targets, low contrast objects, and image texture can be deduced quite readily. <br /><br /> Speckle filtering of medical ultrasound images represents a critical pre-processing step, providing clinicians with enhanced diagnostic ability. Efficient speckle noise removal algorithms may also find applications in real time surgical guidance assemblies. However, it is vital that regions of interests are not compromised during speckle removal. This research pertains to the reduction of speckle noise in ultrasound images while attempting to retain clinical regions of interest. <br /><br /> Recently, the advance of wavelet theory has lead to many applications in noise reduction and compression. Upon investigation of these two divergent fields, it was found that the speckle noise tends to rotate an image's homomorphic complex-wavelet coefficients. This work proposes a new speckle reduction filter involving a counter-rotation of these complex-wavelet coefficients to mitigate the presence of speckle noise. Simulations suggest the proposed denoising technique offers superior visual quality, though its signal-to-mean-square-error ratio (S/MSE) is numerically comparable to adaptive frost and kuan filtering. <br /><br /> This research improves the quality of ultrasound medical images, leading to improved diagnosis for one of the most popular and cost effective imaging modalities used in clinical medicine.

The early detection of prostate cancer plays a significant role in the success of treatment and outcome. To detect prostate cancer, imaging modalities such as TransRectal UltraSound (TRUS) and Magnetic Resonance Imaging (MRI) are relied on. MRI images are more comprehensible than TRUS images which are corrupted by noise such as speckles and shadowing. However, MRI screening is costly, often unavailable in many community hospitals, time consuming, and requires more patient preparation time. Therefore, TRUS is more popular for screening and biopsy guidance for prostate cancer. For these reasons, TRUS images are chosen in this research. Radiologists first segment the prostate image from ultrasound image and then identify the hypoechoic regions which are more likely to exhibit cancer and should be considered for biopsy. In this thesis, the focus is on prostate segmentation and on Regions of Interest (ROI)segmentation. First, the extraneous tissues surrounding the prostate gland are eliminated. Consequently, the process of detecting the cancerous regions is focused on the prostate gland only. Thus, the diagnosing process is significantly shortened. Also, segmentation techniques such as thresholding, region growing, classification, clustering, Markov random field models, artificial neural networks (ANNs), atlas-guided, and deformable models are investigated. In this dissertation, the deformable model technique is selected because it is capable of segmenting difficult images such as ultrasound images. Deformable models are classified as either parametric or geometric deformable models. For the prostate segmentation, one of the parametric deformable models, Gradient Vector Flow (GVF) deformable contour, is adopted because it is capable of segmenting the prostate gland, even if the initial contour is not close to the prostate boundary. The manual segmentation of ultrasound images not only consumes much time and effort, but also leads to operator-dependent results. Therefore, a fully automatic prostate segmentation algorithm is proposed based on knowledge-based rules. The new algorithm results are evaluated with respect to their manual outlining by using distance-based and area-based metrics. Also, the novel technique is compared with two well-known semi-automatic algorithms to illustrate its superiority. With hypothesis testing, the proposed algorithm is statistically superior to the other two algorithms. The newly developed algorithm is operator-independent and capable of accurately segmenting a prostate gland with any shape and orientation from the ultrasound image. The focus of the second part of the research is to locate the regions which are more prone to cancer. Although the parametric dynamic contour technique can readily segment a single region, it is not conducive for segmenting multiple regions, as required in the regions of interest (ROI) segmentation part. Since the number of regions is not known beforehand, the problem is stated as 3D one by using level set approach to handle the topology changes such as splitting and merging the contours. For the proposed ROI segmentation algorithm, one of the geometric deformable models, active contours without edges, is used. This technique is capable of segmenting the regions with either weak edges, or even, no edges at all. The results of the proposed ROI segmentation algorithm are compared with those of the two experts' manual marking. The results are also compared with the common regions manually marked by both experts and with the total regions marked by either expert. The proposed ROI segmentation algorithm is also evaluated by using region-based and pixel-based strategies. The evaluation results indicate that the proposed algorithm produces similar results to those of the experts' manual markings, but with the added advantages of being fast and reliable. This novel algorithm also detects some regions that have been missed by one expert but confirmed by the other. In conclusion, the two newly devised algorithms can assist experts in segmenting the prostate image and detecting the suspicious abnormal regions that should be considered for biopsy. This leads to the reduction the number of biopsies, early detection of the diseased regions, proper management, and possible reduction of death related to prostate cancer.

Ultrasound (US) volume data is noisy, so traditional methods for direct volume rendering (DVR) are less appropriate. Improved methods or new techniques are required. There are furthermore a high performance requirement and limited pre-processing to be considered in order for it to be used interactively, since the volume data might be time-varying. There exist numerous techniques for improving visual perception of volume rendering, and while some perform well and produce a visually enhanced result, many are designed and compared for use with medical data that has a high signal-to-noise ratio. This master thesis describe and compare recent methods for DVR illumination, in the form of ambient occlusion or direct/indirect lighting from an external light source. New designs and modifications are introduced for efficiently and effectively enhancing the visual quality of DVR with US data. Furthermore, this thesis addresses the issue of how clipping is performed during rendering and for the different illumination techniques, which is commonly used in ultrasound visualization. This diploma work was conducted at Siemens Corporate Research in Princeton, NJ where the partially open source framework XIP is developed. The framework was extended further to include modern methods for DVR illumination that are described in detail within this thesis. Finally, presented results show that several methods can be used to visually enhance the visualization within highly interactive frame-rates.