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Full-Text Articles in Engineering
Breast Cancer Risk In Women With Breast Bilateral Asymmetry: Machine Learning Based Risk Analysis And Mitigation Through Developing A Framework For Customized Bra Design, Xi Feng
Electronic Thesis and Dissertation Repository
Breast cancer is the most prevalent form of cancer globally, accounting for 12.5% of all new cases annually. Research has found a significant correlation between breast bilateral asymmetry and an increased risk of cancer, with women diagnosed with breast cancer having higher levels of bilateral asymmetrical breast volume. Unfortunately, 87% of women with breast asymmetry lack adequate tools for assessing their cancer risk. Early screening using bilateral asymmetry to predict a woman's long-term risk of breast cancer can help physicians make informed decisions about whether to recommend sequential imaging and the frequency of screening. Another important factor in understanding the …
Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi
Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi
Electronic Thesis and Dissertation Repository
Chronic Obstructive Pulmonary Disease (COPD) is a condition characterized by persistent inflammation and airflow blockages in the lungs, contributing to a significant number of deaths globally each year. To guide tailored treatment strategies and mitigate future risks, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) employs a multifaceted assessment system of COPD severity, considering patient's lung function, symptoms, and exacerbation history. COPD staging systems, such as the high-resolution eight-stage COPD system and the GOLD 2023 three staging systems, have been later developed based on these factors. Lung Computed Tomography (CT) is becoming increasingly crucial in investigating COPD as it …
Automated Segmentation Of The Inner Ear And Round Window In Computed Tomography Scans Using Convolutional Neural Networks, Kyle A. Rioux
Automated Segmentation Of The Inner Ear And Round Window In Computed Tomography Scans Using Convolutional Neural Networks, Kyle A. Rioux
Electronic Thesis and Dissertation Repository
Computed tomography (CT) scans are acquired prior to cochlear implant (CI) surgery. Three-dimensional segmentations of the inner ear (IE) and round window (RW) based on clinical CTs can improve the CI procedure. Software pipelines are presented here which employ convolutional neural networks to automatically segment the IE and RW. The first pipeline produces high resolution segmentations of the IE and RW in tightly cropped CTs. Mean IE Dice score and RW centroid error were 0.88, 0.57mm and 0.93, 0.18mm in implanted and non-implanted samples, respectively. The second pipeline automatically segments the IE in large field of view CTs of any …
Intraoperative Localization Of Subthalamic Nucleus During Deep Brain Stimulation Surgery Using Machine Learning Algorithms, Mahsa Khosravi
Intraoperative Localization Of Subthalamic Nucleus During Deep Brain Stimulation Surgery Using Machine Learning Algorithms, Mahsa Khosravi
Electronic Thesis and Dissertation Repository
This thesis presents a novel technique for localizing the Subthalamic Nucleus (STN) during Deep Brain Stimulation (DBS) surgery. DBS is an accepted treatment for individuals living with Parkinson's Disease (PD). This surgery involves implantation of a permanent electrode inside the STN to deliver electrical current. The STN is a small grey matter structure within the brain, which makes accurate placement a challenging task for the surgical team. Prior to placement of the permanent electrode, intraoperative microelectrode recordings (MERs) of neural activity are used to localize the STN. The placement of the permanent electrode and the success of the stimulation therapy …