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<p> The allocation of 7.5 GHz of bandwidth by the Federal Communication Commission (FCC) for ultra-wideband (UWB) applications has provided an exciting and a challenging opportunity to design short range wireless communication and microwave imaging systems. To fully realize the potential of the UWB, communication and microwave imaging systems are required to operate over the entire UWB frequency band. The combination of the wide bandwidth requirement and the target application of the UWB systems have led to a surge of interest in designing of novel integrated circuits and antennas for the UWB applications. In any wireless communication and microwave imaging system, the antenna has a fundamental effect on the overall performance of the system, and as a result, it has attracted considerable research interest.</p> <p> This thesis focuses on the design of UWB antennas that are suitable for UWB cancer detection and wireless communication systems. Two planar antennas, one a printed monopole antenna, and the other, a printed slot antenna fed with a coplanar waveguide, are presented in this work. First, the antennas have been designed to operate in air, making them suitable for the UWB wireless short range communication applications. Measurement and simulation results indicate that both antennas achieve input impedance matching in a bandwidth of more than 7.5 GHz. The effect on the input matching of the antennas due to the variation in their geometrical parameters has been studied and both antennas have been fully characterized in air. Next, the two antennas have been redesigned to operate in a coupling medium for medical imaging applications. Both antennas achieve return loss of less than -10 dB over the entire UWB spectrum. Also, the antennas have been fully characterized while operating in the coupling medium and in proximity to a human body model. Finally, a two-element antenna array, based on the printed monopole antenna and the printed slot antenna, in co- and cross-polarized array formation, has been designed. The tumor detection capabilities of all antenna arrays for different scenarios have been studied through electromagnetic simulation and measurements.</p> / Thesis / Master of Applied Science (MASc)

The purpose of this dissertation was to use the technology of text mining and topic modeling to explore unobserved themes of medical case reports that involve medical imaging. Case reports have a valuable place in medical research because they provide educational benefits, offer evidence, and encourage discussions. Their form has evolved throughout the years, but they have remained a key staple in providing important information to the medical communities around the world with educational context and illuminating visuals. Examining medical case reports that have been published throughout the years on multiple medical subjects can be challenging, therefore text mining and topic modeling methods were used to analyze a large set of abstracts from medical case reports involving radiology. The total number of abstracts used for the data analysis was 68,845 that were published between the years 1975 to 2022. The findings indicate that text mining and topic modeling can offer a unique and reproducible approach to examine a large quantity of abstracts for theme analysis.

Laser Speckle Contrast Imaging, or LSCI, is a non-invasive, fast, cheap and easy to use perfusion imaging method which has shown potential in many clinical applications. One problem with the technology however is its limiting field-of-view which results in the physician having to examine and work with multiple images instead of one. In this thesis, a real-time image stitching system was designed with the aim of extending the field of view of LSCI instruments. The system implements a feature-based approach to image registration (SIFT), brute-force matching of features and feather blending. The image transformation is estimated using a statistical methodology (RANSAC) and then validated to improve usability. The evaluation of the system is focused on three key factors: running time of the image stitching algorithm, robustness relative-image pair overlap and usability. The results show that stitching of perfusion images is instantaneous pursuant to human perception for lower resolution images and takes 1.5 to 3.5 seconds for larger resolutions. Stitching is robust given an image-pair overlap of 10% or more, however, temporal noise and sparse environments in perfusion images negatively impacts the systems accuracy and usability. In conclusion, given a contrast-rich region, the system is accurate and easy-to-use such that an untrained user can construct a visually-pleasing panorama that consists of 24 stitched images in approximately 7 minutes.

Yes / The assessment of image quality in medical imaging often requires observers to rate images for some metric or detectability task. These subjective results are used in optimization, radiation dose reduction or system comparison studies and may be compared to objective measures from a computer vision algorithm performing the same task. One popular scoring approach is to use a Likert scale, then assign consecutive numbers to the categories. The mean of these response values is then taken and used for comparison with the objective or second subjective response. Agreement is often assessed using correlation coefficients. We highlight a number of weaknesses in this common approach, including inappropriate analyses of ordinal data and the inability to properly account for correlations caused by repeated images or observers. We suggest alternative data collection and analysis techniques such as amendments to the scale and multilevel proportional odds models. We detail the suitability of each approach depending upon the data structure and demonstrate each method using a medical imaging example. Whilst others have raised some of these issues, we evaluated the entire study from data collection to analysis, suggested sources for software and further reading, and provided a checklist plus flowchart for use with any ordinal data. We hope that raised awareness of the limitations of the current approaches will encourage greater method consideration and the utilization of a more appropriate analysis. More accurate comparisons between measures in medical imaging will lead to a more robust contribution to the imaging literature and ultimately improved patient care. / EU-funded PANORAMA project, funded by grants from Belgium, Italy, France, Netherlands, UK and the ENIAC Joint Undertaking.

Yes / The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radiographer role is lacking. This paper discusses the potential impact of artificial intelligence (AI) on the radiography profession by assessing current workflow and cross-mapping potential areas of AI automation such as procedure planning, image acquisition and processing. We also highlight the opportunities that AI brings including enhancing patient-facing care, increased cross-modality education and working, increased technological expertise and expansion of radiographer responsibility into AI-supported image reporting and auditing roles.

This thesis explores the application of Graph Neural Networks (GNNs), a subset of Geometric Deep Learning methods, for medical image analysis and causal structure learning. Tracking the progression of pathologies in chest radiography poses several challenges in anatomical motion estimation and image registration as this task requires spatially aligning the sequential X-rays and modelling temporal dynamics in change detection. The first part of this thesis proposes a novel approach for change detection in sequential Chest X-ray (CXR) scans using GNNs. The proposed model CheXRelNet utilizes local and global information in CXRs by incorporating intra-image and inter-image anatomical information and showcases an increased downstream performance for predicting the change direction for a pair of CXRs. The second part of the thesis focuses on using GNNs for causal structure learning. The proposed method introduces the concept of intervention on graphs and attempts to relate belief propagation in Bayesian Networks (BN) to message passing in GNNs. Specifically, the proposed method leverages the downstream prediction accuracy of a GNN-based model to infer the correctness of Directed Acyclic Graph (DAG) structures given observational data. Our experimental results do not reveal any correlation between the downstream prediction accuracy of GNNs and structural correctness and hence indicate the harms of directly relating message passing in GNNs to belief propagation in BNs. Overall, this thesis demonstrates the potential of GNNs in medical image analysis and highlights the challenges and limitations of applying GNNs to causal structure learning. / Master of Science / Graphs are a powerful way to represent different real-world data such as interactions between patient observations, co-morbidities, treatments, and relationships between different parts of the human anatomy. They are also a simple and intuitive way of representing causeand- effect relationships between related entities. Graph Neural Networks (GNNs) are neural networks that model such graph-structured data. In this thesis, we explore the applicability of GNNs in analyzing chest radiography and in learning causal relationships. In the first part of this thesis, we propose a method for monitoring disease progression over time in sequential chest X-rays (CXRs). This proposed model CheXRelNet focuses on the interactions within different regions of a CXR and temporal interactions between the same region compared in two CXRs taken at different times for a given patient and accurately predicts the disease progression trend. In the second part of the thesis, we explore if GNNs can be used for identifying causal relationships between covariates. We design a method that uses GNNs for ranking different graph structures based on how well the structures explain the observed data.

Thesis (MScMedSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Background: The assignment of radiation weighting factors to high energy neutron sources is important as there is reason to believe that neutron relative biological effectiveness (RBE) may be related to the inherent radiosensitivity of different individuals. A study was undertaken to quantify the inherent radiosensitivities of lymphocytes obtained from different donors to 60Co y-rays and p(66)/Be neutrons. For this a novel semi-automated image analysis process has been employed. In addition the responses of lymphocytes with different inherent radiosensitivities have also been tested using Auger electrons emitted by 123I. Methods: The RBE of neutrons was determined from dose-response curves for lymphocytes from different donors. Isolated T-lymphocytes irradiated in vitro were cultured to induce micronuclei in binucleated cells and micronuclei (MN) formations numerated using a semi-automated Metafer microscope system. The accuracy in obtaining dose response curves with this method has been tested by evaluating dispersion parameters of MN formations in the response to the different treatment modalities. Differences in the inherent radiosensitivities of cells from different donors were ascertained using 95 % confidence ellipses. [123I]Iododeoxyuridine was prepared in a formulation that allows incorporation of 123I into the DNA of lymphocytes. Micronucleus formations to this treatment were evaluated in lymphocytes with established differences in inherent radiosensitivities. Results: The image analysis system proved to be consistent in detecting micronuclei frequencies in binucleated lymphocytes. As a result, differences in the inherent radiosensitivities of different individuals were distinctive and could be stated at the 95% confidence level. The inter-individual radiosensitivity variations were considerably smaller for blood cells exposed to high energy neutrons compared to 60Co y-rays. Relative biological effectiveness (RBEM) values between 2 and 13 were determined that are highly correlated with the inherent radioresistance of lymphocytes obtained from different individuals. As such radiation weighting factors for high energy neutrons cannot be based on cytogenetic damage determined in lymphocytes from a single donor. Dispersion parameters for micronuclei formations proved to vary according to ionization density. The variation in RBE with neutron dose changed according to theoretical considerations and automated image analysis detection of MN is thus a suitable method to quantify radiation weighting factors. A clear reduction in the variation in radiosensitivity is noted for lymphocytes exposed to Auger electrons compared to 60Co y-rays. The effectiveness of Auger electrons from [123I]IUdR to induce biological damage is demonstrated as the number of disintegrations needed to yield micronuclei formations was found to be more than two orders of magnitude less than that of other compounds. An increase in the RBE of Auger electrons with radioresistance can be inferred from these findings and constitutes a basis for therapeutic gain in treating cells compared to using radioisotopes emitting low-LET radiation. / AFRIKAANSE OPSOMMING: Agtergrond: Die bepaling van straling gewigsfaktore vir hoë energie neutron bronne is belangrik, aangesien daar rede is om te glo dat die relatiewe biologiese effektiwiteit (RBE) kan verband hou met die inherente stralings sensitiwiteit van verskillende individue. Hierdie studie is onderneem om die inherente radiosensitiwiteit van limfosiete verkry vanaf verskillende skenkers te kwantifiseer na blootstelling aan 60Co y -strale en p(66)/Be neutrone. Vir hierdie doel is daar van 'n semi-outomatiese beeldontleding metode gebruik gemaak. Daarbenewens is die reaksie van limfosiete met vooraf bepaalde inherente radiosensitiwiteite ook getoets aan die hand van Auger elektrone wat uitgestraal word deur 123I. Metodiek: Die RBE van neutrone was bepaal uit dosis mikrokerne frekwensie verwantskappe verkry vir limfosiete. Geïsoleerde T-limfosiete was in vitro bestraal en gekweek om mikrokerne te vorm in dubbelkernige selle. Die mikrokerne was gekwantifiseer deur die gebruik van 'n semi-outomatiese Metafer mikroskoop stelsel. Die akkuraatheid in die verkryging van dosis-effek krommes met hierdie metode is getoets deur die ontleding van verspreidings parameters van MN vorming in reaksie op behandeling met die verskillende stralings modaliteite. Verskille in die inherente stralingsensitiwiteite van die selle van verskillende skenkers was vasgestel deur die konstruksie van 95 % betroubaarheidsinterval ellipse. [123I]Iododeoxyuridine was ook berei om 123I in die DNA van limfosiete in te bou. Die mikrokerne vorming op die behandeling is beoordeel in limfosiete met gevestigde verskille in inherent radiosensitiwiteite. Resultate: Die beeld analise stelsel bewys om konsekwent te wees in die opsporing van mikrokerne wat vorm in dubbelkernige limfosiete. Verskille in die inherente radiosensitiwiteite van verskillende skenkers kon vasgestel word op die 95 % betroubaarheidsvlak. Die skommeling in inter-individuele stralings sensitiwiteite was kleiner vir bloed selle blootgestel aan hoë-energie neutrone in vergelyking met 60Co y-strale. Relatiewe biologiese effektiwiteit (RBEM) waardes tussen 2 en 13 is bepaal wat sterk verband hou met die inherente radioweerstandbiedendheid van limfosiete verkry vanaf verskillende persone. As sodanig kan straling gewigsfaktore vir hoë energie neutrone nie gebaseer word op sitogenetiese skade in limfosiete van 'n enkele skenker nie. Verspreidings parameters vir mikrokern vorming het gewissel as ‘n funksie van ionisasiedigtheid van die straling. Die verandering in RBE met neutron dosis verloop volgens teoretiese oorwegings en die semi-outomatiese beeldontledings metode om mikrokerne op te spoor is dus geskik om stralings gewigsfaktore te kwantifiseer. 'n Duidelike afname in die verandering in die stralingsensitiwiteite is waargeneem vir limfosiete blootgestel aan Auger elektrone in vergelyking met 60Co y-strale. Die hoë doeltreffendheid van Auger elektrone afkomstig van [123I]IUdR om biologiese skade te veroorsaak, word weerspieël deur die feit dat die getal disintegrasies wat nodig is om mikrokerne te vorm meer as twee ordes grootte minder is as dié van ander verbindings. 'n Toename in die RBE van Auger elektrone in selle wat radioweerstandbiedend is kan afgelei word uit hierdie bevindinge. Dit vorm 'n basis vir terapeutiese wins in die behandeling van selle in vergelyking met die gebruik van radio-isotope wat lae ionisasie digthede tot stand bring.

<p>It is essential that breast cancer be detected at its earliest stages for better prognosis. Advanced imaging techniques and systems are constantly under development and study to improve the screening and detection of breast cancer. Like every technological advancement in medical care, these techniques and systems need to be tested and verified before their clinical translation. What are currently considered the gold standard for justification of clinical translation are randomized clinical trials. Clinical trials are time-consuming, costly, and expose the population to extra irradiation in the case of x-ray imaging. Given the recent advances in computation and modeling, virtual clinical trials can be carefully designed and carried out to inform, orient, or potentially replace clinical trials given adequate validation and credibility. This dissertation elaborates on the design, implementation, and performance analysis of virtual clinical trials, which is made possible through the employment and advancement of sophisticated tools and models.</p> / Dissertation

abstract: Three dimensional (3-D) ultrasound is safe, inexpensive, and has been shown to drastically improve system ease-of-use, diagnostic efficiency, and patient throughput. However, its high computational complexity and resulting high power consumption has precluded its use in hand-held applications. In this dissertation, algorithm-architecture co-design techniques that aim to make hand-held 3-D ultrasound a reality are presented. First, image enhancement methods to improve signal-to-noise ratio (SNR) are proposed. These include virtual source firing techniques and a low overhead digital front-end architecture using orthogonal chirps and orthogonal Golay codes. Second, algorithm-architecture co-design techniques to reduce the power consumption of 3-D SAU imaging systems is presented. These include (i) a subaperture multiplexing strategy and the corresponding apodization method to alleviate the signal bandwidth bottleneck, and (ii) a highly efficient iterative delay calculation method to eliminate complex operations such as multiplications, divisions and square-root in delay calculation during beamforming. These techniques were used to define Sonic Millip3De, a 3-D die stacked architecture for digital beamforming in SAU systems. Sonic Millip3De produces 3-D high resolution images at 2 frames per second with system power consumption of 15W in 45nm technology. Third, a new beamforming method based on separable delay decomposition is proposed to reduce the computational complexity of the beamforming unit in an SAU system. The method is based on minimizing the root-mean-square error (RMSE) due to delay decomposition. It reduces the beamforming complexity of a SAU system by 19x while providing high image fidelity that is comparable to non-separable beamforming. The resulting modified Sonic Millip3De architecture supports a frame rate of 32 volumes per second while maintaining power consumption of 15W in 45nm technology. Next a 3-D plane-wave imaging system that utilizes both separable beamforming and coherent compounding is presented. The resulting system has computational complexity comparable to that of a non-separable non-compounding baseline system while significantly improving contrast-to-noise ratio and SNR. The modified Sonic Millip3De architecture is now capable of generating high resolution images at 1000 volumes per second with 9-fire-angle compounding. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015