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An Evaluation Of A Deep Learning Approach For Radiation Dose Reduction In 18f-Fdg Pet/Mri Pediatric Epilepsy Imaging, Confidence Raymond
An Evaluation Of A Deep Learning Approach For Radiation Dose Reduction In 18f-Fdg Pet/Mri Pediatric Epilepsy Imaging, Confidence Raymond
Electronic Thesis and Dissertation Repository
Epilepsy is a degenerative brain disease characterized by abruption of neural activities that result in seizures. The onset of epileptic seizures are usually from a primary source - the epileptogenic foci (EF) which could be distributed to nearby neurons and tissues. Accurate localization of EF is critical in epilepsy cases where drug treatment has failed, and surgery is indicated to resect the EF to alleviate seizure. Typically, hybrid positron emission tomography (PET) and computed tomography (CT) imaging are performed to functionally localize the EF in drug-resistant epilepsy for surgical planning when anatomical abnormalities representing the EF cannot be identified on …
Machine Learning Towards General Medical Image Segmentation, Clara Tam
Machine Learning Towards General Medical Image Segmentation, Clara Tam
Electronic Thesis and Dissertation Repository
The quality of patient care associated with diagnostic radiology is proportionate to a physician's workload. Segmentation is a fundamental limiting precursor to diagnostic and therapeutic procedures. Advances in machine learning aims to increase diagnostic efficiency to replace single applications with generalized algorithms. We approached segmentation as a multitask shape regression problem, simultaneously predicting coordinates on an object's contour while jointly capturing global shape information. Shape regression models inherent point correlations to recover ambiguous boundaries not supported by clear edges and region homogeneity. Its capabilities was investigated using multi-output support vector regression (MSVR) on head and neck (HaN) CT images. Subsequently, …
Retrospective Motion Correction In Magnetic Resonance Imaging Of The Brain, Patricia Johnson
Retrospective Motion Correction In Magnetic Resonance Imaging Of The Brain, Patricia Johnson
Electronic Thesis and Dissertation Repository
Magnetic Resonance Imaging (MRI) is a tremendously useful diagnostic imaging modality that provides outstanding soft tissue contrast. However, subject motion is a significant unsolved problem; motion during image acquisition can cause blurring and distortions in the image, limiting its diagnostic utility. Current techniques for addressing head motion include optical tracking which can be impractical in clinical settings due to challenges associated with camera cross-calibration and marker fixation. Another category of techniques is MRI navigators, which use specially acquired MRI data to track the motion of the head.
This thesis presents two techniques for motion correction in MRI: the first is …