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Full-Text Articles in Engineering
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, …
Objective Estimation Of Tracheoesophageal Speech Quality, Yousef S Ettomi Ali
Objective Estimation Of Tracheoesophageal Speech Quality, Yousef S Ettomi Ali
Electronic Thesis and Dissertation Repository
Speech quality estimation for pathological voices is becoming an increasingly important research topic. The assessment of the quality and the degree of severity of a disordered speech is important to the clinical treatment and rehabilitation of patients. In particular, patients who have undergone total laryngectomy (larynx removal) produce Tracheoesophageal (TE) speech. In this thesis, we study the problem of TE speech quality estimation using advanced signal processing approaches. Since it is not possible to have a reference (clean) signal corresponding to a given TE speech (disordered) signal, we investigate in particular the non-intrusive techniques (also called single-ended or blind approaches) …
Process Analytics From Passive Acoustic Emissions Monitoring During Fluidized Bed Pellet Coating In Pharmaceutical Manufacturing, Allan Carter
Electronic Thesis and Dissertation Repository
Piezoelectric microphones were attached to a top spray fluidized bed to provide valuable process signatures. Relationships were developed between sound waves and conditions within the fluidized bed to relay critical quality and performance information. Deep learning analytics were used to extract valuable information from experimental data. Advancements in passive acoustic emissions monitoring will play a key role in optimizing pharmaceutical manufacturing pathways to ensure drug quality and performance.