Automatic facial analysis for objective assessment of facial paralysis

Facial Paralysis is a condition causing decreased movement on one side of the face. A quantitative, objective and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents an approach based on the automatic analysis of patient video data. Facial feature localization and facial movement detection methods are discussed. An algorithm is presented to process the optical flow data to obtain the motion features in the relevant facial regions. Three classification methods are applied to provide quantitative evaluations of regional facial nerve function and the overall facial nerve function based on the House-Brackmann Scale. Experiments show the Radial Basis Function (RBF) Neural Network to have superior performance

Deep metric learning to rank

We propose a novel deep metric learning method by revisiting the learning to rank approach. Our method, named FastAP, optimizes the rank-based Average Precision measure, using an approximation derived from distance quantization. FastAP has a low complexity compared to existing methods, and is tailored for stochastic gradient descent. To fully exploit the benefits of the ranking formulation, we also propose a new minibatch sampling scheme, as well as a simple heuristic to enable large-batch training. On three few-shot image retrieval datasets, FastAP consistently outperforms competing methods, which often involve complex optimization heuristics or costly model ensembles.Accepted manuscrip

Analytical applications of ionic liquids and determination of cell viability using capillary electrophoresis coupled with laser-induced fluorescence detection

Newly developed ionic liquids that are air and moisture stable have been subject to an increasing number of scientific investigations. Their recent applications include novel solvent systems and catalysts for organic synthesis, versatile electrolytes for electrochemical studies, and liquid-liquid extraction solvents. The potential usage of ionic liquids could be vast. The purpose of the first part of this dissertation is to address the novel applications of ionic liquids in the field of analytical chemistry. In this part, the author\u27s research can be divided into two directions: (a) examining the chromatographic performance of ionic liquids as gas chromatography (GC) stationary phases or solvents for GC stationary phases; (b) synthesizing new ionic liquids and testing their properties as matrices for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry.;In addition to multiple applications of ionic liquids, we also became interested in developing an effective instrumental method to assess the viability of microorganisms and mammalian cells. Since existing techniques, such as plate count methods, flow cytometry, etc., are either laborious or too expensive, highly efficient and more affordable methods are needed. Therefore, the second part of this dissertation is focused on the feasibility of using capillary electrophoresis (CE), in combination with fluorescent labeling technique, to determine cell viability. The author first adapted the recently developed highly efficient microbial CE method and viable fluorescence staining method to determine the viability of bacteria and yeast, and then carried out the potency study of animal sperm using a similar CE approach.;This dissertation is presented as two independent parts. Each part begins with a general introduction and literature review of recent progress in the specific research area. The following chapters are arranged in such a way that the related published papers or manuscripts are presented as separate chapters. All these chapters are presented in publication format. References for each chapter are independent and appear at the end of the chapter. The last chapter is general conclusions covering both parts of this dissertation

Vibrio harveyi: a serious pathogen of fish and invertebrates in mariculture

Vibrio harveyi, which belongs to family Vibrionaceae of class Gammaproteobacteria, includes the species V. carchariae and V. trachuri as its junior synonyms. The organism is a well-recognized and serious bacterial pathogen of marine fish and invertebrates, including penaeid shrimp, in aquaculture. Diseased fish may exhibit a range of lesions, including eye lesions/blindness, gastro-enteritis, muscle necrosis, skin ulcers, and tail rot disease. In shrimp, V. harveyi is regarded as the etiological agent of luminous vibriosis in which affected animals glow in the dark. There is a second condition of shrimp known as Bolitas negricans where the digestive tract is filled with spheres of sloughed-off tissue. It is recognized that the pathogenicity mechanisms of V. harveyi may be different in fish and penaeid shrimp. In shrimp, the pathogenicity mechanisms involved the endotoxin lipopolysaccharide, and extracellular proteases, and interaction with bacteriophages. In fish, the pathogenicity mechanisms involved extracellular hemolysin (encoded by duplicate hemolysin genes), which was identified as a phospholipase B and could inactivate fish cells by apoptosis, via the caspase activation pathway. V. harveyi may enter the so-called viable but nonculturable (VBNC) state, and resuscitation of the VBNC cells may be an important reason for vibriosis outbreaks in aquaculture. Disease control measures center on dietary supplements (including probiotics), nonspecific immunostimulants, and vaccines and to a lesser extent antibiotics and other antimicrobial compounds

Biomedical image sequence analysis with application to automatic quantitative assessment of facial paralysis

Facial paralysis is a condition causing decreased movement on one side of the face. A quantitative, objective, and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents an approach based on the automatic analysis of patient video data. Facial feature localization and facial movement detection methods are discussed. An algorithm is presented to process the optical flow data to obtain the motion features in the relevant facial regions. Three classification methods are applied to provide quantitative evaluations of regional facial nerve function and the overall facial nerve function based on the House-Brackmann scale. Experiments show the radial basis function (RBF) neural network to have superior performance

Biomedical image sequence analysis with application to automatic quantitative assessment of facial paralysis

Facial paralysis is a condition causing decreased movement on one side of the face. A quantitative, objective, and reliable assessment system would be an invaluable tool for clinicians treating patients with this condition. This paper presents an approach based on the automatic analysis of patient video data. Facial feature localization and facial movement detection methods are discussed. An algorithm is presented to process the optical flow data to obtain the motion features in the relevant facial regions. Three classification methods are applied to provide quantitative evaluations of regional facial nerve function and the overall facial nerve function based on the House-Brackmann scale. Experiments show the radial basis function (RBF) neural network to have superior performance