Biomedical Commons^™

In-Situ Gold-Ceria Nanoparticles: Superior Optical Fluorescence Quenching Sensor For Dissolved Oxygen, Nader Shehata, Ishac Kandas, Effat Samir

Electrical & Computer Engineering Faculty Publications

Cerium oxide (ceria) nanoparticles (NPs) have been proved to be an efficient optical fluorescent material through generating visible emission (~530 nm) under violet excitation. This feature allowed ceria NPs to be used as an optical sensor via the fluorescence quenching Technique. In this paper, the impact of in-situ embedded gold nanoparticles (Au NPs) inside ceria nanoparticles was studied. Then, gold–ceria NPs were used for sensing dissolved oxygen (DO) in aqueous media. It was observed that both fluorescence intensity and lifetime were changed due to increased concentration of DO. Added gold was found to enhance the sensitivity of ceria to DO …

Low Temperature Plasma Jets: Characterization And Biomedical Applications, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

No abstract provided.

Prefrontal High Gamma In Ecog Tags Periodicity Of Musical Rhythms In Perception And Imagination, S.A. Herff, C. Herff, A. J. Milne, Garett D. Johnson, J. J. Shih, D. J. Krusienski

Electrical & Computer Engineering Faculty Publications

Rhythmic auditory stimuli are known to elicit matching activity patterns in neural populations. Furthermore, recent research has established the particular importance of high-gamma brain activity in auditory processing by showing its involvement in auditory phrase segmentation and envelope tracking. Here, we use electrocorticographic (ECoG) recordings from eight human listeners to see whether periodicities in high-gamma activity track the periodicities in the envelope of musical rhythms during rhythm perception and imagination. Rhythm imagination was elicited by instructing participants to imagine the rhythm to continue during pauses of several repetitions. To identify electrodes whose periodicities in high-gamma activity track the periodicities in …

Mitochondrial Utilization Of Competing Fuels Is Altered In Insulin Resistant Skeletal Muscle Of Non-Obese Rats (Goto-Kakizaki), Nicola Lai, Ciarán E. Fealy, Chinna M. Kummitha, Silvia Cabras, John P. Kirwan, Charles L. Hoppel

Electrical & Computer Engineering Faculty Publications

Aim: Insulin-resistant skeletal muscle is characterized by metabolic inflexibility with associated alterations in substrate selection, mediated by peroxisome-proliferator activated receptor 𝜹 (PPAR𝜹). Although it is established that PPAR𝜹 contributes to the alteration of energy metabolism, it is not clear whether it plays a role in mitochondrial fuel competition. While nutrient overload may impair metabolic flexibility by fuel congestion within mitochondria, in absence of obesity defects at a mitochondrial level have not yet been excluded. We sought to determine whether reduced PPAR𝜹 content in insulin-resistant rat skeletal muscle of a non-obese rat model of T2DM (Goto-Kakizaki, GK) ameliorate the inhibitory effect …

Bioenergetic Functions In Subpopulations Of Heart Mitochondria Are Preserved In A Non-Obese Type 2 Diabetes Rat Model (Goto-Kakizaki), Nicola Lai, C. M. Kummitha, F. Loy, R. Isola, C. L. Hoppel

Electrical & Computer Engineering Faculty Publications

A distinct bioenergetic impairment of heart mitochondrial subpopulations in diabetic cardiomyopathy is associated with obesity; however, many type 2 diabetic (T2DM) patients with high-risk for cardiovascular disease are not obese. In the absence of obesity, it is unclear whether bioenergetic function in the subpopulations of mitochondria is affected in heart with T2DM. To address this issue, a rat model of non-obese T2DM was used to study heart mitochondrial energy metabolism, measuring bioenergetics and enzyme activities of the electron transport chain (ETC). Oxidative phosphorylation in the presence of substrates for ETC and ETC activities in both populations of heart mitochondria in …

Deep Learning With Context Encoding For Semantic Brain Tumor Segmentation And Patient Survival Prediction, Linmin Pei, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

One of the most challenging problems encountered in deep learning-based brain tumor segmentation models is the misclassification of tumor tissue classes due to the inherent imbalance in the class representation. Consequently, strong regularization methods are typically considered when training large-scale deep learning models for brain tumor segmentation to overcome undue bias towards representative tissue types. However, these regularization methods tend to be computationally exhaustive, and may not guarantee the learning of features representing all tumor tissue types that exist in the input MRI examples. Recent work in context encoding with deep CNN models have shown promise for semantic segmentation of …

1995-2005: A Decade Of Innovation In Low Temperature Plasma And Its Applications, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

Scientific breakthroughs tend to come in spurts when unique societal, economical, and political circumstances conspire (knowingly or unknowingly) and create an environment ripe for creativity. The field of low temperature plasma (LTP) recently experienced such an upheaval, which this paper attempts to relate in some details. There have been “roadmap” papers published before, which look towards the future of the field, but all roads start somewhere and even “new” roads are often paved over older roads that were discovered and traveled by early pioneers. With the sharp decrease in funding for fusion research in the USA in the early 1990s …

Microstructural Evaluation Of Aluminium Alloy A365 T6 In Machining Operation, Bankole I. Oladapo, S. Abolfazl Zahedi, Francis T. Omigbodun, Edwin A. Oshin, Victor A. Adebiyi, Olaoluwa B. Malachi

Electrical & Computer Engineering Faculty Publications

The optimum cutting parameters such as cutting depth, feed rate, cutting speed and magnitude of the cutting force for A356 T6 was determined concerning the microstructural detail of the material. Novel test analyses were carried out, which include mechanical evaluation of the materials for density, glass transition temperature, tensile and compression stress, frequency analysis and optimisation as well as the functional analytic behaviour of the samples. The further analytical structure of the particle was performed, evaluating the surface luminance structure and the profile structure. The cross-sectional filter profile of the sample was extracted, and analyses of Firestone curve for the …

Perspective: The Physics, Diagnostics, And Applications Of Atmospheric Pressure Low Temperature Plasma Sources Used In Plasma Medicine, M. Laroussi

Electrical & Computer Engineering Faculty Publications

Low temperature plasmas have been used in various plasma processing applications for several decades. But it is only in the last thirty years or so that sources generating such plasmas at atmospheric pressure in reliable and stable ways have become more prevalent. First, in the late 1980s, the dielectric barrier discharge was used to generate relatively large volume diffuse plasmas at atmospheric pressure. Then, in the early 2000s, plasma jets that can launch cold plasma plumes in ambient air were developed. Extensive experimental and modeling work was carried out on both methods and much of the physics governing such sources …

Experimental Assessment Of Mouse Sociability Using An Automated Image Processing Approach, Frency Varghese, Jessica A. Burket, Andrew D. Benson, Stephen I. Deutsch, Christian W. Zemlin

Electrical & Computer Engineering Faculty Publications

Mouse is the preferred model organism for testing drugs designed to increase sociability. We present a method to quantify mouse sociability in which the test mouse is placed in a standardized apparatus and relevant behaviors are assessed in three different sessions (called session I, II, and III). The apparatus has three compartments (see Figure 1), the left and right compartments contain an inverted cup which can house a mouse (called “stimulus mouse”). In session I, the test mouse is placed in the cage and its mobility is characterized by the number of transitions made between compartments. In session II, a …

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. …

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 …

Plasma Processes And Cancer - Special Topical Cluster Of The 2nd Iwpct Meeting, Masaru Hori, Mounir Laroussi, Kai Masur, Yuzuru Ikehara

Electrical & Computer Engineering Faculty Publications

(First paragraph) Although the emerging multidisciplinary field of plasma medicine has been around for nearly two decades important advances have already taken place that could one day revolutionize healthcare and the way various challenging diseases can be treated.1-3Amongst these advances the effects of low temperature plasma (LTP) on cancer cells in vitro and in vivo stand out.4-13Current cancer treatment modalities, such as chemotherapy and radiation therapy, have serious side effects and tend to lose their benefits to the patients after a while. Therefore, novel and improved therapies that can be used alone …

Application And Histology-Driven Refinement Of Active Contour Models To Functional Region And Nerve Delineation: Towards A Digital Brainstem Atlas, Nimal Patel, Sharmin Sultana, Tanweer Rashid, Dean Krusienski, Michel A. Audette

Electrical & Computer Engineering Faculty Publications

This paper presents a methodology for the digital formatting of a printed atlas of the brainstem and the delineation of cranial nerves from this digital atlas. It also describes on-going work on the 3D resampling and refinement of the 2D functional regions and nerve contours. In MRI-based anatomical modeling for neurosurgery planning and simulation, the complexity of the functional anatomy entails a digital atlas approach, rather than less descriptive voxel or surface-based approaches. However, there is an insufficiency of descriptive digital atlases, in particular of the brainstem. Our approach proceeds from a series of numbered, contour-based sketches coinciding with slices …

Direct Classification Of All American English Phonemes Using Signals From Functional Speech Motor Cortex, Emily M. Mugler, James L. Patton, Robert D. Flint, Zachary A. Wright, Stephan U. Schuele, Joshua Rosenow, Jerry J. Shih, Dean J. Krusienski, Marc W. Slutzky

Electrical & Computer Engineering Faculty Publications

Although brain-computer interfaces (BCIs) can be used in several different ways to restore communication, communicative BCI has not approached the rate or efficiency of natural human speech. Electrocorticography (ECoG) has precise spatiotemporal resolution that enables recording of brain activity distributed over a wide area of cortex, such as during speech production. In this study, we investigated words that span the entire set of phonemes in the General American accent using ECoG with 4 subjects. We classified phonemes with up to 36% accuracy when classifying all phonemes and up to 63% accuracy for a single phoneme. Further, misclassified phonemes follow articulation …

Numerical Study Of Lipid Translocation Driven By Nanoporation Due To Multiple High-Intensity, Ultrashort Electrical Pulses, Viswanadham Sridhara, Ravindra P. Joshi

Electrical & Computer Engineering Faculty Publications

The dynamical translocation of lipids from one leaflet to another due to membrane permeabilization driven by nanosecond, high-intensity (>100 kV/cm) electrical pulses has been probed. Our simulations show that lipid molecules can translocate by diffusion through water-filled nanopores which form following high voltage application. Our focus is on multiple pulsing, and such simulations are relevant to gauge the time duration over which nanopores might remain open, and facilitate continued lipid translocations and membrane transport. Our results are indicative of a N^1/2 scaling with pulse number for the pore radius. These results bode well for the use of pulse …

Tpm: Cloud-Based Tele Ptsd Monitor Using Multi-Dimensional Information, Roger Xu, Gang Mei, Guangfan Zhang, Pan Gao, Aaron Pepe, Jiang Li, James D. Westwood (Ed.), Susan W. Westwood (Ed.), Li Felländer-Tsai (Ed.), Randy S. Haluck (Ed.), Richard A. Robb (Ed.), Steven Senger (Ed.), Kirby G. Vosburgh (Ed.)

Electrical & Computer Engineering Faculty Publications

An automated system that can remotely and non-intrusively screen individuals at high risk for Post-Traumatic Stress Disorder (PTSD) and monitor their progress during treatment would be desired by many Veterans Affairs (VAs) as well as other PTSD treatment and research organizations. In this paper, we present an automated, cloud-based Tele-PTSD Monitor (TPM) system based on the fusion of multiple sources of information. The TPM system can be hosted in a cloud environment and accessed through landline or cell phones, or on the Internet through a web portal or mobile application (app).

Brain-Computer Interfaces In Medicine, Jerry J. Shih, Dean J. Krusienski, Johnathan R. Wolpaw

Electrical & Computer Engineering Faculty Publications

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroenceph-alography-based spelling and single-neuron-based device control, researchers have gone on to use electroenceph-alographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces …

Signals From Intraventricular Depth Electrodes Can Control A Brain-Computer Interface, Jerry J. Shih, Dean J. Krusienski

Electrical & Computer Engineering Faculty Publications

A Brain-Computer Interface (BCI) is a device that enables severely disabled people to communicate and interact with their environments using their brain waves. Most research investigating BCI in humans have used scalp-recorded electroencephalography (EEG). We have recently demonstrated that signals from intracranial electrocorticography (ECoG) and stereotactic depth electrodes (SDE) in the hippocampus can be used to control a BCI P300 Speller paradigm. We report a case in which stereotactic depth electrodes positioned in the ventricle were able to obtain viable signals for a BCI. Our results demonstrate that event-related potentials from intraventricular electrodes can be used to reliably control the …

Fusion Of Visual And Thermal Images Using Genetic Algorithms, Sertan Erkanli, Jiang Li, Ender Oguslu, Shangce Gao (Ed.)

Electrical & Computer Engineering Faculty Publications

No abstract provided.

Procedural Wound Geometry And Blood Flow Generation For Medical Training Simulators, Rifat Aras, Yuzhong Shen, Jiang Li, David R. Holmes Iii (Ed.), Kenneth H. Wong (Ed.)

Electrical & Computer Engineering Faculty Publications

Efficient application of wound treatment procedures is vital in both emergency room and battle zone scenes. In order to train first responders for such situations, physical casualty simulation kits, which are composed of tens of individual items, are commonly used. Similar to any other training scenarios, computer simulations can be effective means for wound treatment training purposes. For immersive and high fidelity virtual reality applications, realistic 3D models are key components. However, creation of such models is a labor intensive process. In this paper, we propose a procedural wound geometry generation technique that parameterizes key simulation inputs to establish the …

A Voice-Based Automated System For Ptsd Screening And Monitoring, Roger Xu, Gang Mei, Guangfan Zhang, Pan Gao, Timothy Judkins, Michael Cannizzaro, Jiang Li, James D. Westwood (Ed.), Susan W. Westwood (Ed.), Li Felländer-Tsai (Ed.), Randy S. Haluck (Ed.), Richard A. Robb (Ed.), Steven Senger (Ed.), Kirby G. Vosburgh (Ed.)

Electrical & Computer Engineering Faculty Publications

Comprehensive evaluation of PTSD includes diagnostic interviews, self-report testing, and physiological reactivity measures. It is often difficult and costly to diagnose PTSD due to patient access and the variability in symptoms presented. Additionally, potential patients are often reluctant to seek help due to the stigma associated with the disorder. A voice-based automated system that is able to remotely screen individuals at high risk for PTSD and monitor their symptoms during treatment has the potential to make great strides in alleviating the barriers to cost effective PTSD assessment and progress monitoring. In this paper we present a voice-based automated Tele-PTSD Monitor …

2d Face Database Diversification Based On 3d Face Modeling, Qun Wang, Jiang Li, Vijayan K. Asari, Mohammad A. Karim, Manuel Filipe Costa (Ed.)

Electrical & Computer Engineering Faculty Publications

Pose and illumination are identified as major problems in 2D face recognition (FR). It has been theoretically proven that the more diversified instances in the training phase, the more accurate and adaptable the FR system appears to be. Based on this common awareness, researchers have developed a large number of photographic face databases to meet the demand for data training purposes. In this paper, we propose a novel scheme for 2D face database diversification based on 3D face modeling and computer graphics techniques, which supplies augmented variances of pose and illumination. Based on the existing samples from identical individuals of …

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% …

Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)

Electrical & Computer Engineering Faculty Publications

At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, …

On The Visual Quality Enhancement Of Super-Resolution Images, Amr Hussein Yousef, Jiang Li, Mohammad Karim, Andrew G. Tescher (Ed.)

Electrical & Computer Engineering Faculty Publications

Super-resolution (SR) is the process of obtaining a higher resolution image from a set of lower resolution (LR) blurred and noisy images. One may, then, envision a scenario where a set of LR images is acquired with a sensor on a moving platform. In such a case, an SR image can be reconstructed in an area of sufficient overlap between the LR images which generally have a relative shift with respect to each other by subpixel amounts. The visual quality of the SR image is affected by many factors such as the optics blur, the inherent signalto- noise ratio of …

An Integrated Computer-Aided Robotic System For Dental Implantation, Xiaoyan Sun, Yongki Yoon, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

This paper describes an integrated system for dental implantation including both preoperative planning utilizing computer-aided technology and automatic robot operation during the intra-operative stage. A novel two-step registration procedure was applied for transforming the preoperative plan to the operation of the robot, with the help of a Coordinate Measurement Machine (CMM). Experiments with a patient-specific phantom were carried out to evaluate the registration error for both position and orientation. After adopting several improvements, registration accuracy of the system was significantly improved. Sub-millimeter accuracy with the Target Registration Errors (TREs) of 0.38±0.16 mm (N=5) was achieved. The target orientation errors after …

Prediction Of Brain Tumor Progression Using A Machine Learning Technique, Yuzhong Shen, Debrup Banerjee, Jiang Li, Adam Chandler, Yufei Shen, Frederic D. Mckenzie, Jihong Wang, Nico Karssemeijer (Ed.), Ronald M. Summers (Ed.)

Electrical & Computer Engineering Faculty Publications

A machine learning technique is presented for assessing brain tumor progression by exploring six patients' complete MRI records scanned during their visits in the past two years. There are ten MRI series, including diffusion tensor image (DTI), for each visit. After registering all series to the corresponding DTI scan at the first visit, annotated normal and tumor regions were overlaid. Intensity value of each pixel inside the annotated regions were then extracted across all of the ten MRI series to compose a 10 dimensional vector. Each feature vector falls into one of three categories:normal, tumor, and normal but progressed to …

Prostate Cancer Region Prediction Using Maldi Mass Spectra, Ayyappa Vadlamudi, Shao-Hui Chuang, Xiaoyan Sun, Lisa Cazares, Julius Nyalwidhe, Dean Troyer, O. John Semmes, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

For the early detection of prostate cancer, the analysis of the Prostate-specific antigen (PSA) in serum is currently the most popular approach. However, previous studies show that 15% of men have prostate cancer even their PSA concentrations are low. MALDI Mass Spectrometry (MS) proves to be a better technology to discover molecular tools for early cancer detection. The molecular tools or peptides are termed as biomarkers. Using MALDI MS data from prostate tissue samples, prostate cancer biomarkers can be identified by searching for molecular or molecular combination that can differentiate cancer tissue regions from normal ones. Cancer tissue regions are …

Optimizing Computer-Aided Colonic Polyp Detection For Ct Colonography By Evolving The Pareto Front, Jiang Li, Adam Huang, Jack Tao, Jiamin Liu, Robert L. Van Uitert, Nicholas Petrick, Ronald Summers

Electrical & Computer Engineering Faculty Publications

A multiobjective genetic algorithm is designed to optimize a computer-aided detection (CAD) system for identifying colonic polyps. Colonic polyps appear as elliptical protrusions on the inner surface of the colon. Curvature-based features for colonic polyp detection have proved to be successful in several CT colonography (CTC) CAD systems. Our CTC CAD program uses a sequential classifier to form initial polyp detections on the colon surface. The classifier utilizes a set of thresholds on curvature-based features to cluster suspicious colon surface regions into polyp candidates. The thresholds were previously chosen experimentally by using feature histograms. The chosen thresholds were effective for …