Biomedical Engineering and Bioengineering Commons^™

Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various types of human actions and human poses.

The proposed algorithm uses the combination of an auto-encoder based action association framework which produces per-frame probability estimates of the action being performed, and a pose recognition framework which gives per-frame body part locations.

The main focus in this manuscript is to effectively combine these per-frame action probability estimates and pose trajectories from a short temporal window to obtain mid-level features. We demonstrate that these mid-level …

Novel Incorportation Of Biomedical Engineering Algorithms (Bispectral Index Guided Or Anesthetic Concentration Guided) In Real-Time Decision Support To Prevent Intraoperative Awareness Using An Electronic Anesthesia Information Mananagement System, Amy Melanie Shanks

Wayne State University Dissertations

Background: Intraoperative awareness with explicit recall (AWR) is a feared complication of surgery that can lead to significant psychological distress. Several large prospective trials have been completed comparing two methods of monitoring anesthetic depth [minimum alveolar concentration (MAC) or electroencephalography (EEG) monitoring using the bispectral index (BIS)] for the prevention of AWR. However, these trials were conducted in high risk populations, limiting generalizability.

Research Hypothesis: Real-time decision support with Anesthesia Information Management System alerts based on a novel anesthetic concentration algorithm (incorporating the use of intravenous anesthetics) or an EEG-guided algorithm will reduce the known incidence of AWR.

Methods: First, …

Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger

Williams Honors College, Honors Research Projects

This Honors Project focused on a few aspects of this topic. The second is comparing the molecular signature kernels to three of the BLOSUM matrices (30, 62, and 90) to test the accuracy of the mathematical model. The kernel matrix was manipulated in order to improve the relationship by focusing on side groups and also by changing how the structure was represented in the matrix by increasing the initial height distance from the central atom (Height 1 and Height 2 included).

There were multiple design constraints for this project. The first was the comparison with the BLOSUM matrices (30, 62, …

Multi-Surface Simplex Spine Segmentation For Spine Surgery Simulation And Planning, Rabia Haq

Computational Modeling & Simulation Engineering Theses & Dissertations

This research proposes to develop a knowledge-based multi-surface simplex deformable model for segmentation of healthy as well as pathological lumbar spine data. It aims to provide a more accurate and robust segmentation scheme for identification of intervertebral disc pathologies to assist with spine surgery planning. A robust technique that combines multi-surface and shape statistics-aware variants of the deformable simplex model is presented. Statistical shape variation within the dataset has been captured by application of principal component analysis and incorporated during the segmentation process to refine results. In the case where shape statistics hinder detection of the pathological region, user-assistance is …

Adaptive Graph Construction For Isomap Manifold Learning, Loc Tran, Zezhong Zheng, Guoquing Zhou, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the ℓ₁ norm. The ℓ₁ enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than …

A Comparative Study Of Two Prediction Models For Brain Tumor Progression, Deqi Zhou, Loc Tran, Jihong Wang, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images.

We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. …

Designing A Biomimetic Testing Platform For Actuators In A Series-Elastic Co-Contraction System, Ryan Tyler Schroeder

UNLV Theses, Dissertations, Professional Papers, and Capstones

Actuators determine the performance of robotic systems at the most intimate of levels. As a result, much work has been done to assess the performance of different actuator systems. However, biomimetics has not previously been utilized as a pretext for tuning a series elastic actuator system with the purpose of designing an empirical testing platform. Thus, an artificial muscle tendon system has been developed in order to assess the performance of two distinct actuator types: (1) direct current electromagnetic motors and (2) ultrasonic rotary piezoelectric motors. Because the design of the system takes advantage of biomimetic operating principles such as …

Preliminary Test Of A Real-Time, Interactive Silent Speech Interface Based On Electromagnetic Articulograph, Jun Wang, Ashok Samal, Jordan R. Green

School of Computing: Conference and Workshop Papers

A silent speech interface (SSI) maps articulatory movement data to speech output. Although still in experimental stages, silent speech interfaces hold significant potential for facilitating oral communication in persons after laryngectomy or with other severe voice impairments. Despite the recent efforts on silent speech recognition algorithm development using offline data analysis, online test of SSIs have rarely been conducted. In this paper, we present a preliminary, online test of a real-time, interactive SSI based on electromagnetic motion tracking. The SSI played back synthesized speech sounds in response to the user’s tongue and lip movements. Three English talkers participated in this …

An Analysis Of Eye Movements With Helmet Mounted Displays, Kalyn A. Tung

Theses and Dissertations

Helmet or Head-Mounted Displays (HMD) applications have expanded to include a range from advanced military cockpits to consumer glasses. However, users have documented loss of legibility while undergoing vibration. Recent research indicates that undesirable eye movement is related to the vibration frequency a user experiences. In vibrating environments, two competing eye reflexes likely contribute to eye movements. The Vestibulo-ocular Reflex responds to motion sensed in the otoliths while the pursuit reflex is driven by the visual system to maintain the desired image on the fovea. This study attempts to isolate undesirable eye motions that occur while using a HMD by …

Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo

Masters Theses

"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …

A Nonrigid Registration Method For Correcting Brain Deformation Induced By Tumor Resection, Yixun Liu, Chengjun Yao, Fotis Drakopoulos, Jinsong Wu, Liangfu Zhou, Nikos Chrisochoides

Computer Science Faculty Publications

Purpose: This paper presents a nonrigid registration method to align preoperative MRI with intraoperative MRI to compensate for brain deformation during tumor resection. This method extends traditional point-based nonrigid registration in two aspects: (1) allow the input data to be incomplete and (2) simulate the underlying deformation with a heterogeneous biomechanical model.

Methods: The method formulates the registration as a three-variable (point correspondence, deformation field, and resection region) functional minimization problem, in which point correspondence is represented by a fuzzy assign matrix; Deformation field is represented by a piecewise linear function regularized by the strain energy of a heterogeneous biomechanical …

Coupling Graphs, Efficient Algorithms And B-Cell Epitope Prediction, Liang Zhao, Steven C. H. Hoi, Zhenhua Li, Limsoon Wong, Hung Nguyen

Research Collection School Of Computing and Information Systems

Coupling graphs are newly introduced in this paper to meet many application needs particularly in the field of bioinformatics. A coupling graph is a two-layer graph complex, in which each node from one layer of the graph complex has at least one connection with the nodes in the other layer, and vice versa. The coupling graph model is sufficiently powerful to capture strong and inherent associations between subgraph pairs in complicated applications. The focus of this paper is on mining algorithms of frequent coupling subgraphs and bioinformatics application. Although existing frequent subgraph mining algorithms are competent to identify frequent subgraphs …

Protein Loop Length Estimation From Medium Resolution Cryoem Images, Andrew R. Mcknight

Computer Science Theses & Dissertations

In the post-genomic era, proteomics research presents a new frontier in life science. Proteins play roles in virtually every biological process, and understanding their atomic structures is the key to unraveling how they carry out their work. Compared to the over half million protein sequences in UniProt, only around 25,000 unique sequences have been atomically modeled and deposited to PDB (Protein Databank). Cryoelectron Microscopy (cryoEM) is an important biophysical technique that produces 3D subnanometer resolution images of molecules not amenable to past approaches like x-ray crystallography or nuclear magnetic resonance. De novo modeling is becoming a promising approach to derive …

An Investigation And Analysis Of The Vestibulo-Ocular Reflex In A Vibration Environment, Daniel J. Uribe

Theses and Dissertations

Forty years of innovations have greatly improved Helmet-Mounted Displays (HMDs) and their integration into military systems. However, a significant issue with HMDs is the effect of vibration and the associated Vestibulo-Ocular Reflex (VOR). When a human’s head is subject to low-frequency vibration, the VOR stabilizes the eye with respect to objects in the external environment. However, this response is inappropriate in HMDs as the display moves with the user’s head and the VOR blurs the image as it is projected on the human retina. Current compensation techniques suggest increasing the size of displayed graphics or text to compensate for the …

Nonlinear Granger Causality And Its Application In Decoding Of Human Reaching Intentions, Mengting Liu

Doctoral Dissertations

Multi-electrode recording is a key technology that allows the brain mechanisms of decision making, cognition, and their breakdown in diseases to be studied from a network perspective. As the hypotheses concerning the role of neural interactions in cognitive paradigms become increasingly more elaborate, the ability to evaluate the direction of neural interactions in neural networks holds the key to distinguishing their functional significance.

Granger Causality (GC) is used to detect the directional influence of signals between multiple locations. To extract the nonlinear directional flow, GC was completed through a nonlinear predictive approach using radial basis functions (RBF). Furthermore, to obtain …

Visual Exploration And Information Analytics Of High-Dimensional Medical Images, Darshan Pai

Wayne State University Dissertations

Data visualization has transformed how we analyze increasingly large and complex data sets. Advanced visual tools logically represent data in a way that communicates the most important information inherent within it and culminate the analysis with an insightful conclusion. Automated analysis disciplines - such as data mining, machine learning, and statistics - have traditionally been the most dominant fields for data analysis. It has been complemented with a near-ubiquitous adoption of specialized hardware and software environments that handle the storage, retrieval, and pre- and postprocessing of digital data. The addition of interactive visualization tools allows an active human participant in …

Whole-Word Recognition From Articulatory Movements For Silent Speech Interfaces, Jun Wang, Ashok Samal, Jordan R. Green, Frank Rudzicz

Department of Special Education and Communication Disorders: Faculty Publications

Articulation-based silent speech interfaces convert silently produced speech movements into audible words. These systems are still in their experimental stages, but have significant potential for facilitating oral communication in persons with laryngectomy or speech impairments. In this paper, we report the result of a novel, real-time algorithm that recognizes whole-words based on articulatory movements. This approach differs from prior work that has focused primarily on phoneme-level recognition based on articulatory features. On average, our algorithm missed 1.93 words in a sequence of twenty-five words with an average latency of 0.79 seconds for each word prediction using a data set of …

Role Of Glutathione In Lung Retention Of 99mtc-Hexamethylpropyleneamine Oxime In Two Unique Rat Models Of Hyperoxic Lung Injury, Said H. Audi, David L. Roerig, Steven Thomas Haworth, Anne V. Clough

Biomedical Engineering Faculty Research and Publications

Rat exposure to 60% O₂ for 7 days (hyper-60) or to >95% O₂ for 2 days followed by a 24-hour in room air (hyper-95R) confers susceptibility or tolerance, respectively, of the otherwise lethal effects of subsequent exposure to 100% O₂. The objective of this study was to determine if lung retention of the radiopharmaceutical agent ^99mTc-HMPAO (hexamethylpropyleneamine oxime) is differentially altered in hyper-60 and hyper-95R rats. Tissue retention of HMPAO is dependent on intracellular content of the antioxidant glutathione (GSH) and mitochondrial function. HMPAO was injected i.v. in anesthetized rats and planar images were acquired. …

Real-Time Face Detection And Recognition, Parker Hill, Brendan Morris

College of Engineering: Graduate Celebration Programs

The face has become a popular biometric for identification due to the wide range of features and difficulty in manipulation of the metric. In order to work towards a robust facial recognition system, this work contains a foundation for using the face as a recognition metric. First, faces are detected from still images using a Viola-Jones object detection algorithm. Then, Eigenfaces is applied to the detected faces. The system was tested on face databases as well as real-time feed from a web camera.

Image-Guided Robotic Dental Implantation With Natural-Root-Formed Implants, Xiaoyan Sun

Electrical & Computer Engineering Theses & Dissertations

Dental implantation is now recognized as the standard of the care for tooth replacement. Although many studies show high short term survival rates greater than 95%, long term studies (> 5 years) have shown success rates as low as 41.9%. Reasons affecting the long term success rates might include surgical factors such as limited accuracy of implant placement, lack of spacing controls, and overheating during the placement.

In this dissertation, a comprehensive solution for improving the outcome of current dental implantation is presented, which includes computer-aided preoperative planning for better visualization of patient-specific information and automated robotic site-preparation for superior …

Mathematical Model Development Of Super-Resolution Image Wiener Restoration, Amr H. Yousef, Jiang Li, Mohammad A. Karim

Electrical & Computer Engineering Faculty Publications

In super-resolution (SR), a set of degraded low-resolution (LR) images are used to reconstruct a higher-resolution image that suffers from acquisition degradations. One way to boost SR images visual quality is to use restoration filters to remove reconstructed images artifacts. We propose an efficient method to optimally allocate the LR pixels on the high-resolution grid and introduce a mathematical derivation of a stochastic Wiener filter. It relies on the continuous-discrete-continuous model and is constrained by the periodic and nonperiodic interrelationships between the different frequency components of the proposed SR system. We analyze an end-to-end model and formulate the Wiener filter …

Fast Stochastic Wiener Filter For Super-Resolution Image Restoration With Information Theoretic Visual Quality Assessment, Amr Hussein Yousef, Jiang Li, Mohammad Karim, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)

Electrical & Computer Engineering Faculty Publications

Super-resolution (SR) refers to reconstructing a single high resolution (HR) image from a set of subsampled, blurred and noisy low resolution (LR) images. The reconstructed image suffers from degradations such as blur, aliasing, photo-detector noise and registration and fusion error. Wiener filter can be used to remove artifacts and enhance the visual quality of the reconstructed images. In this paper, we introduce a new fast stochastic Wiener filter for SR reconstruction and restoration that can be implemented efficiently in the frequency domain. Our derivation depends on the continuous-discrete-continuous (CDC) model that represents most of the degradations encountered during the image-gathering …

A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal, Sarah M. Asio

Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research

The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To …

Learning Feature Dependencies For Noise Correction In Biomedical Prediction, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

The presence of noise or errors in the stated feature values of biomedical data can lead to incorrect prediction. We introduce a Bayesian Network-based Noise Correction framework named BN-NC. After data preprocessing, a Bayesian Network (BN) is learned to capture the feature dependencies. Using the BN to predict each feature in turn, BN-NC estimates a feature's error rate as the deviation between its predicted and stated values in the training data, and allocates the appropriate uncertainty to its subsequent findings during prediction. BN-NC automatically generates a probabilistic rule to explain BN prediction on the class variable using the feature values …

A Secure Behavior Modification Sensor System For Physical Activity Improvement, Alan Price

CGU Theses & Dissertations

Today, advances in wireless sensor networks are making it possible to capture large amounts of information about a person and their interaction within their home environment. However, what is missing is how to ensure the security of the collected data and its use to alter human behavior for positive benefit.

In this research, exploration was conducted involving the "infrastructure" and "intelligence" aspects of a wireless sensor network through a Behavior Modification Sensor System. First was to understand how a secure wireless sensor network could be established through the symmetric distribution of keys (the securing of the infrastructure), and it involves …

Heterogeneous Modeling Of Medical Image Data Using B-Spline Functions, Olya Grove

USF Tampa Graduate Theses and Dissertations

Ongoing developments in the field of medical imaging modalities have pushed the frontiers of modern medicine and biomedical engineering, prompting the need for new applications to improve diagnosis, treatment and prevention of diseases.

Biomedical data visualization and modeling rely predominately on manual processing and utilization of voxel and facet based homogeneous models. Biological structures are naturally heterogeneous and in order to accurately design and biomimic biological structures, properties such as chemical composition, size and shape of biological constituents need to be incorporated in the computational biological models.

Our proposed approach involves generating a density point cloud based on the intensity …

Bcc Skin Cancer Diagnosis Based On Texture Analysis Techniques, Shao-Hui Chuang, Xiaoyan Sun, Wen-Yu Chang, Gwo-Shing Chen, Adam Huang, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% …

Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)

Electrical & Computer Engineering Faculty Publications

In a recent study [1], we investigated the feasibility of predicting brain tumor progression based on multiple MRI series and we tested our methods on seven patients' MRI images scanned at three consecutive visits A, B and C. Experimental results showed that it is feasible to predict tumor progression from visit A to visit C using a model trained by the information from visit A to visit B. However, the trained model failed when we tried to predict tumor progression from visit B to visit C, though it is clinically more important. Upon a closer look at the MRI scans …

Automatic Detection Of Aircraft Emergency Landing Sites, Yu-Fei Shen, Zia-Ur Rahman, Dean Krusienski, Jiang Li, Zia-Ur Rahman (Ed.), Stephen E. Reichenbach (Ed.), Mark Allen Neifeld (Ed.)

Electrical & Computer Engineering Faculty Publications

An automatic landing site detection algorithm is proposed for aircraft emergency landing. Emergency landing is an unplanned event in response to emergency situations. If, as is unfortunately usually the case, there is no airstrip or airfield that can be reached by the un-powered aircraft, a crash landing or ditching has to be carried out. Identifying a safe landing site is critical to the survival of passengers and crew. Conventionally, the pilot chooses the landing site visually by looking at the terrain through the cockpit. The success of this vital decision greatly depends on the external environmental factors that can impair …

Modeling And Quantitative Analysis Of White Matter Fiber Tracts In Diffusion Tensor Imaging, Xuwei Liang

University of Kentucky Doctoral Dissertations

Diffusion tensor imaging (DTI) is a structural magnetic resonance imaging (MRI) technique to record incoherent motion of water molecules and has been used to detect micro structural white matter alterations in clinical studies to explore certain brain disorders. A variety of DTI based techniques for detecting brain disorders and facilitating clinical group analysis have been developed in the past few years. However, there are two crucial issues that have great impacts on the performance of those algorithms. One is that brain neural pathways appear in complicated 3D structures which are inappropriate and inaccurate to be approximated by simple 2D structures, …