Bioimaging and Biomedical Optics Commons^™

Enhancement Of Deep Learning Protein Structure Prediction, Ruoming Shen

Modeling, Simulation and Visualization Student Capstone Conference

Protein modeling is a rapidly expanding field with valuable applications in the pharmaceutical industry. Accurate protein structure prediction facilitates drug design, as extensive knowledge about the atomic structure of a given protein enables scientists to target that protein in the human body. However, protein structure identification in certain types of protein images remains challenging, with medium resolution cryogenic electron microscopy (cryo-EM) protein density maps particularly difficult to analyze. Recent advancements in computational methods, namely deep learning, have improved protein modeling. To maximize its accuracy, a deep learning model requires copious amounts of up-to-date training data.

This project explores DeepSSETracer, a …

Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna

Electrical Engineering Theses

This thesis presents a study on the optical characteristics of hollow-core photonic crystal fibers (HC-PCFs) with a band gap cladding structure and their applications in optical fiber sensing. This 800B HC-PCF exhibited excellent optical properties and has a flexible structure, which makes them suitable for a wide range of industrial applications. Finite element simulations and structural optimization designs were conducted using the surface plasmon resonance (SPR) technique to determine the optimal performance parameters of the 800B HC-PCF. The fiber was further modified using the SPR technique to improve its practical detection capabilities. The performance of the modified fiber was observed …

Evaluating Human Eye Features For Objective Measure Of Working Memory Capacity, Yasasi Abeysinghe, Enkelejda Kasneci (Ed.), Frederick Shic (Ed.), Mohamed Khamis (Ed.)

Computer Science Faculty Publications

Eye tracking measures can provide means to understand the underlying development of human working memory. In this study, we propose to develop machine learning algorithms to find an objective relationship between human eye movements via oculomotor plant and their working memory capacity, which determines subjective cognitive load. Here we evaluate oculomotor plant features extracted from saccadic eye movements, traditional positional gaze metrics, and advanced eye metrics such as ambient/focal coefficient , gaze transition entropy, low/high index of pupillary activity (LHIPA), and real-time index of pupillary activity (RIPA). This paper outlines the proposed approach of evaluating eye movements for obtaining an …

Ultrasensitive Tapered Optical Fiber Refractive Index, Erem Ujah, Meimei Lai, Gymama Slaughter

Electrical & Computer Engineering Faculty Publications

Refractive index (RI) sensors are of great interest for label-free optical biosensing. A tapered optical fiber (TOF) RI sensor with micron-sized waist diameters can dramatically enhance sensor sensitivity by reducing the mode volume over a long distance. Here, a simple and fast method is used to fabricate highly sensitive refractive index sensors based on localized surface plasmon resonance (LSPR). Two TOFs (l = 5 mm) with waist diameters of 5 µm and 12 µm demonstrated sensitivity enhancement at λ = 1559 nm for glucose sensing (5-45 wt%) at room temperature. The optical power transmission decreased with increasing glucose concentration due …

Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving …

The Role Of Generative Adversarial Networks In Bioimage Analysis And Computational Diagnostics., Ahmed Naglah

Electronic Theses and Dissertations

Computational technologies can contribute to the modeling and simulation of the biological environments and activities towards achieving better interpretations, analysis, and understanding. With the emergence of digital pathology, we can observe an increasing demand for more innovative, effective, and efficient computational models. Under the umbrella of artificial intelligence, deep learning mimics the brain’s way in learn complex relationships through data and experiences. In the field of bioimage analysis, models usually comprise discriminative approaches such as classification and segmentation tasks. In this thesis, we study how we can use generative AI models to improve bioimage analysis tasks using Generative Adversarial Networks …

Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biological understanding of complex diseases such as stroke and obesity is critical for the advancement of medicine. Further knowledge discovery can provide effective biomarkers to improve disease diagnosis and prognosis, identify driver mutations, predict individual genetic susceptibility for early prevention and effective disease management, and facilitate development of personalized drugs. Stroke is the second leading cause of death and long-term disability in the world. Thus, stroke management is a time-sensitive emergency. The initial hours after stroke onset map the trajectory of subsequent neurologic complications. Cerebral edema develops hours to days after acute ischemic stroke and may result in midline shift …

Evaluation And Clinical Implementation Of A Dual-Energy Ct Stopping-Power Ratio Mapping Technique For Proton-Therapy Treatment Planning, Maria Jose Medrano Matamoros

McKelvey School of Engineering Graduate Student Theses & Dissertations

Proton radiotherapy has the potential to treat tumors with better conformal dose distribution than competing modalities when the rapid dose falloff at the end of the proton-beam range is correctly aligned to the edge of the clinical target volume (CTV). However, its clinical potential is dependent on the accurate localization of the Bragg-peak position from predicted stopping-power ratio maps. The method that is most commonly used in today’s clinical practice for predicting stopping-power ratio (SPR) consists of a stoichiometric calibrationtechnique based on single-energy CT (SECT) for direct estimation of patient-specific SPR distribution from vendor-reconstructed Hounsfield Unit (HU) images. Unfortunately, this …

Advancing The Portability, Field Of View, And Spatiotemporal Resolution Of Multi-Parametric Photoacoustic Microscopy, Fenghe Zhong

McKelvey School of Engineering Graduate Student Theses & Dissertations

Capable of structural, functional, molecular, and metabolic imaging with high spatial resolution in vivo, photoacoustic microscopy (PAM) is an emerging tool in biomedical research. Further, recent advances in multi-parametric acquisition and analysis make PAM uniquely capable of simultaneously mapping the total concentration of hemoglobin (CHb), oxygen saturation of hemoglobin (sO2), and blood flow speed. However, there are multiple major limitations, including, the large footprint, low imaging speed, limited imaging contrast, and insufficient axial resolution, which impedance its applications in basic and translational research. In this dissertation, I presented potential solutions to overcome the limitations above.In the first part of this …

The Effects Of Metronomic And Maximum-Tolerated Dose Chemotherapy In Colorectal Cancer Angiogenesis: A Combined Approach Using Endoscopic Diffuse Reflectance Spectroscopy And Mrna Expression, Ariel Isaac Mundo Ortiz

Graduate Theses and Dissertations

Colorectal cancer (CRC) continues to be one of the most incident and deadliest types of cancer worldwide. Chemotherapy has proven effective to reduce tumor burden for CRC patients, but there are several disadvantages associated with the use of mainstay maximtolerated dose (MTD) chemotherapeutic strategies. Metronomic chemotherapy (MET) has been developed as an alternative that addresses the shortcomings of maximum-tolerated dose chemotherapy but so far its effectiveness as a neoadjuvant strategy for CRC has not been explored.

This dissertation uses a combined optics and molecular biology approach (using diffuse reflectance spectroscopy and mRNA expression) to study the changes in angiogenesis and …

Analysis Of An Existing Method In Refinement Of Protein Structure Predictions Using Cryo-Em Images, Maytha Alshammari, Jing He, Willy Wriggers, Jiangwen Sun

College of Sciences Posters

Protein structure prediction produces atomic models from its amino acid sequence. Three-dimensional structures are important for understanding the function mechanism of proteins. Knowing the structure of a given protein is crucial in drug development design of novel enzymes. AlphaFold2 is a protein structure prediction tool with good performance in recent CASP competitions. Phenix is a tool for determination of a protein structure from a high-resolution 3D molecular image. Recent development of Phenix shows that it is capable to refine predicted models from AlphaFold2, specifically the poorly predicted regions, by incorporating information from the 3D image of the protein. The goal …

Two-Stage Transfer Learning For Facial Expression Classification In Children, Gregory Hubbard, Megan Witherow, Khan Iftekharuddin

Undergraduate Research Symposium

Studying facial expressions can provide insight into the development of social skills in children and provide support to individuals with developmental disorders. In afflicted individuals, such as children with Autism Spectrum Disorder (ASD), atypical interpretations of facial expressions are well-documented. In computer vision, many popular and state-of-the-art deep learning architectures (VGG16, EfficientNet, ResNet, etc.) are readily available with pre-trained weights for general object recognition. Transfer learning utilizes these pre-trained models to improve generalization on a new task. In this project, transfer learning is implemented to leverage the pretrained model (general object recognition) on facial expression classification. Though this method, the …

Design And Development Of Software With A Graphical User Interface To Display And Convert Multiple Microscopic Histology Images, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Histological images are widely used to assess the microscopic anatomy of biological tissues. Recent advancements in image analysis allow the identification of structural features on histological sections that can help advance medical device development, brain and cancer research, drug discovery, vascular mechanobiology, and many other fields. Histological slide scanners create images in SVS and TIFF formats that were designed to archive image blocks and high-resolution textual information. Because these formats were primarily intended for storage, they are often not compatible with conventional image analysis software and require conversion before they can be used in research. We have developed a user-friendly …

Resolving The Three-Dimensional Rotational And Translational Dynamics Of Single Molecules Using Radially And Azimuthally Polarized Fluorescence, Oumeng Zhang, Weiyan Zhou, Jin Lu, Tingting Wu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We report a radially and azimuthally polarized (raPol) microscope for high detection and estimation performance in single-molecule orientation-localization microscopy (SMOLM). With 5000 photons detected from Nile red (NR) transiently bound within supported lipid bilayers (SLBs), raPol SMOLM achieves 2.9 nm localization precision, 1.5° orientation precision, and 0.17 sr precision in estimating rotational wobble. Within DPPC SLBs, SMOLM imaging reveals the existence of randomly oriented binding pockets that prevent NR from freely exploring all orientations. Treating the SLBs with cholesterol-loaded methyl-β-cyclodextrin (MβCD-chol) causes NR’s orientational diffusion to be dramatically reduced, but curiously NR’s median lateral displacements drastically increase from 20.8 to …

Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter

Wayne State University Dissertations

Presented in this work is an investigation of the application of artificially intelligent algorithms, namely deep learning, to generate segmentations for the application in functional avoidance radiotherapy treatment planning. Specific applications of deep learning for functional avoidance include generating hippocampus segmentations from computed tomography (CT) images and generating synthetic pulmonary perfusion images from four-dimensional CT (4DCT).A single institution dataset of 390 patients treated with Gamma Knife stereotactic radiosurgery was created. From these patients, the hippocampus was manually segmented on the high-resolution MR image and used for the development of the data processing methodology and model testing. It was determined that …

Biomedical Applications Of Lanthanide Nanomaterials, For Imaging, Sensing And Therapy, Qize Zhang, Stephen O'Brien, Jan Grimm

Publications and Research

The application of nanomaterials made of rare earth elements within biomedical sciences continues to make significant progress. The rare earth elements, also called the lanthanides, play an essential role in modern life through materials and electronics. As we learn more about their utility, function, and underlying physics, we can contemplate extending their applications to biomedicine. This particularly applies to diagnosis and radiation therapy due to their relatively unique features, such as an ultra-wide Stokes shift in the luminescence, variable magnetism and potentially tunable properties, due to the library of lanthanides available and their multivalent oxidation state chemistry. The ability to …

Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Within condensed matter, single fluorophores are sensitive probes of their chemical environments, but it is difficult to use their limited photon budget to image precisely their positions, 3D orientations, and rotational diffusion simultaneously. We demonstrate the polarized vortex point spread function (PSF) for measuring these parameters, including characterizing the anisotropy of a molecule’s wobble, simultaneously from a single image. Even when imaging dim emitters (∼500 photons detected), the polarized vortex PSF can obtain 12 nm localization precision, 4°–8° orientation precision, and 26° wobble precision. We use the vortex PSF to measure the emission anisotropy of fluorescent beads, the wobble dynamics …

Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu

Dissertations

Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …

Using Deep Learning To Analyze Materials In Medical Images, Carson Molder

Computer Science and Computer Engineering Undergraduate Honors Theses

Modern deep learning architectures have become increasingly popular in medicine, especially for analyzing medical images. In some medical applications, deep learning image analysis models have been more accurate at predicting medical conditions than experts. Deep learning has also been effective for material analysis on photographs. We aim to leverage deep learning to perform material analysis on medical images. Because material datasets for medicine are scarce, we first introduce a texture dataset generation algorithm that automatically samples desired textures from annotated or unannotated medical images. Second, we use a novel Siamese neural network called D-CNN to predict patch similarity and build …

Development Of Quantitative Ultrasound-Mediated Molecular Imaging Of The Tumor Microenvironment, Trevor Mitcham

Dissertations and Theses (Open Access)

While conventional diagnostic imaging modalities provide anatomical information to clinicians, these techniques are not sensitive to critical physiological processes. In order to properly classify cancer, it is necessary to investigate noninvasive methods which can provide insight into these processes, allowing clinicians to determine personalized therapeutic options. Therefore, molecular imaging is focused on visualization and characterization of biomarkers within the tumor microenvironment (TME), which can then be combined with the anatomical information provided from diagnostic imaging.

Two such biomarkers of interest are blood oxygen saturation (SO₂) and cell receptor expression. SO₂ is a measure of the fraction of …

Biomedical Applications And Syntheses Of Selected Anthraquinone Dyes, Richard Sirard

Senior Honors Theses

Anthraquinones are aromatic organic compounds that have multiple applications in the biomedical field. Some anthraquinone-based compounds are used as fluorophores to contrast cell nuclei while others act as chemotherapeutic agents. However, there are not many fluorescent anthraquinone cell stains currently available. In this study, commercially available anthraquinone dyes, in addition to other dye families and compounds, were reviewed for their unique properties, advantages, and drawbacks. The development and characterization of three novel anthraquinone fluorophores revealed promising photophysical characteristics, like large Stokes shifts. One of the compounds, RBS3, was chosen for fixed and live cell staining and exhibited desirable biomedical properties. …

An Improved Clipped Sub-Histogram Equalization Technique Using Optimized Local Contrast Factor For Mammogram Image Analysis, Nurshafira Hazim Chan

Student Works (2020-2029)

Mammography has been known worldwide as the most common imaging modalities utilized for early detection of breast cancer. The mammographic images produced are in greyscale, however they often produced poor contrast images, non-uniform illumination, and the image often contain artefacts and noise. These limitations can be overcame during the pre-processing stage by improving the image enhancement process. Therefore, in this research an optimized enhancement framework is developed where the local contrast factor is manipulated to preserve details of the image. This technique aims to improve the overall image visibility without altering histogram of the original image, which will affect the …

Deep Learning-Based Breast Cancer Detection And Classification Using Histopathology Images, Ghulam Murtaza

Student Works (2020-2029)

Cancer disease is drastically increasing worldwide over the past few years. Among all types of cancers in women, breast cancer (BrC) is the main cause of abnormal deaths. For a confident diagnosis of BrC, histopathology (Hp) images are usually suggested by the doctors. BrC detection is a diagnostic test for benign (non-cancerous) and malignant (cancerous) breast tumors (BrT). Once the BrT is diagnosed, then it needs to be classified for subtypes of benign and malignant to start specific treatment. Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training …

Computational Modelling Enables Robust Multidimensional Nanoscopy, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

The following sections are included:

• Present State of Computational Modelling in Fluorescence Nanoscopy

• Recent Contributions to Computational Modelling in Fluorescence Nanoscopy

• Outlook on Computational Modelling in Fluorescence Nanoscopy

• Acknowledgments

• References

Three-Dimensional (3d) Reconstruction Of Computer Tomography Cardiac Images Using Visualization Toolkit (Vtk), Mohammad Zahid Zamaludin

Student Works (2020-2029)

Cardiac study proves to be important to diagnose and treat cardiovascular disease that accounts for 20% of death in the world. Three-dimensional (3D) images of the heart are important to understand its real structure, functions and physical abnormalities occurring in the tissue. The objective of this paper is to reconstruct 3D images from 2D CT Scan slices of the cardiac region of interest using Visualisation Toolkit (VTK). The Visualization Toolkit (VTK) is non-propriety software with state-of-the-art tools for 3D rendering that is easily customizable programming. 3D images are reconstructed using surface rendering technique and volume rendering technique. Volume rendering shows …

Perceptually Improved Medical Image Translations Using Conditional Generative Adversarial Networks, Anurag Vaidya

Honors Theses

Magnetic resonance imaging (MRI) can help visualize various brain regions. Typical MRI sequences consist of T1-weighted sequence (favorable for observing large brain structures), T2-weighted sequence (useful for pathology), and T2-FLAIR scan (useful for pathology with suppression of signal from water). While these different scans provide complementary information, acquiring them leads to acquisition times of ~1 hour and an average cost of $2,600, presenting significant barriers. To reduce these costs associated with brain MRIs, we present pTransGAN, a generative adversarial network capable of translating both healthy and unhealthy T1 scans into T2 scans. We show that the addition of non-adversarial …

Clinical Applications And Feasibility Of Proton Ct And Proton Radiography, Christina Marie Sarosiek

Graduate Research Theses & Dissertations

Proton therapy is a form of radiation treatment for cancer that utilizes the Bragg peak to create conformal high dose regions around the tumor volume. However, the use of x-ray computed tomography (CT) and x-ray radiography for treatment planning and pre-treatment quality assurance procedures improves the achievable effectiveness of proton treatment plans (using proton CT) and the pretreatment verification (using proton radiography). Errors in the conversion from x-ray Hounsfield units (HU) to proton relative stopping powers (RSP) leads to errors in the predicted proton range. To account for the errors, 3.5% margins are included in the treatment plan. This means …

Fmri Feature Extraction Model For Adhd Classification Using Convolutional Neural Network, Senuri De Silva, Sanuwani Udara Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, Sampath Jayarathna

Computer Science Faculty Publications

Biomedical intelligence provides a predictive mechanism for the automatic diagnosis of diseases and disorders. With the advancements of computational biology, neuroimaging techniques have been used extensively in clinical data analysis. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder, with the symptomology of inattention, impulsivity, and hyperactivity, in which early diagnosis is crucial to prevent unwelcome outcomes. This study addresses ADHD identification using functional magnetic resonance imaging (fMRI) data for the resting state brain by evaluating multiple feature extraction methods. The features of seed-based correlation (SBC), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) are comparatively applied to …

Combining Cryo-Em Density Map And Residue Contact For Protein Secondary Structure Topologies, Maytha Alshammari, Jing He

Computer Science Faculty Publications

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments and a set of traces of secondary structures in three-dimensional space. In order to enhance accuracy in ranking secondary structure topologies, we explored a method that combines three sources of information: a set …

Single‐Molecule 3d Orientation Imaging Reveals Nanoscale Compositional Heterogeneity In Lipid Membranes, Jin Lu, Hesam Mazidi, Tianben Ding, Oumeng Zhang, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

In soft matter, thermal energy causes molecules to continuously translate and rotate, even in crowded environments, thereby impacting the spatial organization and function of most molecular assemblies, such as lipid membranes. Directly measuring the orientation and spatial organization of large collections (>3000 molecules μm⁻²) of single molecules with nanoscale resolution remains elusive. In this paper, we utilize SMOLM, single‐molecule orientation localization microscopy, to directly measure the orientation spectra (3D orientation plus “wobble”) of lipophilic probes transiently bound to lipid membranes, revealing that Nile red's (NR) orientation spectra are extremely sensitive to membrane chemical composition. SMOLM images resolve …