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Application of Artificial Intelligence in Hip Ultrasound and its Performance in Detecting Developmental Dysplasia of the Hip
DownloadSpring 2022
Developmental Dysplasia of Hip (DDH) which represents a wide range of abnormalities from acetabular dysplasia to fixed dislocation, is mainly defined by a loss of conformity between the femoral head and the acetabulum and it can lead to structural instability and osteoarthritis. The diagnosis of...
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Spring 2024
As cancer is the leading global cause of death, an ongoing challenge is predicting an individual's cancer progression accurately, to facilitate personalized treatment planning. Individuals diagnosed with cancer may succumb to the illness or face cancer recurrence post-treatment. The first part of...
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Fall 2017
For cancer research, a powerful imaging modality for both preclinical (where the focus is on imaging small animals) and clinical (where the focus is on imaging human subjects) applications should be inexpensive, portable, noninvasive, safe, and capable of measuring a myriad of information....
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2019-01-01
Vadim Bulitko, Sean Caulfield, Astrid Ensslin, Daniel Evans, Gillian Harvey, Scott Smallwood, Daniel Laforest, Brad Necyk, Marilène Oliver, Aidan Rowe, Isabelle Van Grimde, Jonathan Garfinkel, Tess Heinricks, Marilene Oliver, Blaine Campbell
DYSCORPIA: Future Intersections of the Body and Technology was a two-year interdisciplinary research project that brought together scholars from art and design, music, digital and medical humanities, radiology, computer science and contemporary dance in order to question what it means not to know...
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Fall 2016
Accurate information is the foundation of correct clinical diagnoses. Physicians are increasingly relying on new devices and tools to improve the quality of information used in their decision making. Wrong, misleading, or hard to interpret data can prevent patients from receiving proper...
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Extending Differentiable Programming to include Non-differentiable Modules using Differentiable Bypass for Combining Convolutional Neural Networks and Dynamic Programming into an End-to-end Trainable Framework
DownloadSpring 2019
Differentiable Programming is the paradigm where different functions or modules are combined into a unified pipeline with the purpose of applying end-to-end learning or optimization. A natural impediment is the non-differentiability characteristic of many modules. This thesis proposes a new way...
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Image Registration with Homography: A Refresher with Differentiable Mutual Information, Ordinary Differential Equation and Complex Matrix Exponential
DownloadFall 2020
This work presents a novel method of tackling the task of image registration. Our algorithm uses a differentiable form of Mutual Information implemented via a neural network called MINE. An important property of neural networks is them being differentiable, which allows them to be used as a loss...
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Novel 3D Ultrasound Imaging Techniques Using Top-Orthogonal-to-Bottom-Electrode (TOBE) Arrays
DownloadFall 2019
Ultrasound imaging is a safe, affordable and reliable diagnostic tool widely used in medical professions. While 2D ultrasound imaging is used extensively in clinical environments, 3D ultrasound imaging has not yet seen wide clinical acceptance. This is partly due to the practical limitations on...
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Spring 2018
Quantitative relaxation mapping allows for direct non-invasive tissue quantification with removal of variations arising from RF fields and non-uniform coil sensitivity profiles. T2 may be quantified using multi-echo spin echo sequences; however, in practical imaging situations, imperfect...
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Spring 2015
Image texture is defined as visual patterns appearing in images. The powerful perceptive capability of texture features has made texture analysis a major research topic in computer vision and image processing. Texture features are used to detect defective products in factories, to understand...