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Bioimaging and Biomedical Optics Commons

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Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian 2025 Guangzhou Huashang College

Adaptive Fusion Neural Networks For Sparse-Angle X-Ray 3d Reconstruction, Shaoyong Hong, Bo Yang, Yan Chen, Hao Quan, Shan Liu, Minyi Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

3D medical image reconstruction has significantly enhanced diagnostic accuracy, yet the reliance on densely sampled projection data remains a major limitation in clinical practice. Sparse-angle X-ray imaging, though safer and faster, poses challenges for accurate volumetric reconstruction due to limited spatial information. This study proposes a 3D reconstruction neural network based on adaptive weight fusion (AdapFusionNet) to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images. To address the issue of spatial inconsistency in multi-angle image reconstruction, an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion, thereby improving …


A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian 2025 Guangzhou Huashong College

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …


Ai-Driven Approach For Diagnosis Of Renal Transplant Rejection Based On Biomarkers Identification And Integration., Israa Sharaby 2024 University of Louisville

Ai-Driven Approach For Diagnosis Of Renal Transplant Rejection Based On Biomarkers Identification And Integration., Israa Sharaby

Electronic Theses and Dissertations

They kidney is a vital organ for which humans are fortunate to find a spare through transplantation to sustain critical body functions, offering a hope to those struggling with renal failure. Kidney transplant procedure is the optimal treatment for people who suffer from end-stage renal failure. However, there are posed challenges due to the risk of immune rejection and the limited availability of donors. Early detection of renal rejection can provide timely intervention and accurate diagnosis that are critical to improve the transplant outcomes. This study explores the innovative approaches for addressing the current challenges through biomarkers identification, imaging techniques, …


Hypoxic Incubator: Improving Robustness/Reliability And Demonstrating Physiological Efficacy, Damon Dennis Tan 2024 California Polytechnic State University, San Luis Obispo

Hypoxic Incubator: Improving Robustness/Reliability And Demonstrating Physiological Efficacy, Damon Dennis Tan

Master's Theses

The Microphysiological Systems Laboratory aims to develop colorectal cancer tumor models under a hypoxic environment to assess model response to pharmaceutical compounds in vitro. To perform relevant studies, researchers have attempted to use different hypoxic inducing strategies such as a nitrogen pod and hypoxic incubator to recreate in vivo physiological responses to hypoxia. However, studies would be interrupted due to incubator functionality failure. To ensure successful and physiologically relevant studies, I improved and verified the robustness and reliability of a hypoxic incubator previously designed and manufactured in the lab. Through the testing and iterating design processes, I engineered and implemented …


Real-Time Navigation System For Breast Cancer Surgery With Pre- And Intra-Operative Imaging Using Neural Networks, Motaz Alqaoud 2024 Old Dominion University

Real-Time Navigation System For Breast Cancer Surgery With Pre- And Intra-Operative Imaging Using Neural Networks, Motaz Alqaoud

Biomedical Engineering Theses & Dissertations

Breast cancer is one of the most frequently diagnosed malignancies in women worldwide, necessitating precise diagnosis and treatment. Breast-conserving surgery (BCS) is the primary treatment for nonpalpable cases, yet current approaches often lack accuracy due to the absence of real-time 3D imaging during surgery. This limitation impairs surgeons’ ability to visualize tumor locations, compromising outcomes and potentially leading to repeat surgeries with higher risks, undesirable cosmetic results, increased costs, and, in some cases, mastectomy. Thus, there is a critical need for a navigation system to facilitate accurate tumor excision in nonpalpable breast cancer through real-time patient-specific 3D tracking.

This study …


Denoising And Super-Resolution Of In-Vitro 4e Flow Mri In A Stenotic Phantom Model Using Physics-Informed Neural Networks., Shrouk M. Wally 2024 University of Louisville

Denoising And Super-Resolution Of In-Vitro 4e Flow Mri In A Stenotic Phantom Model Using Physics-Informed Neural Networks., Shrouk M. Wally

Electronic Theses and Dissertations

In recent years, the use of 4D flow MRI has revolutionized cardiovascular imag- ing by providing comprehensive data on blood flow dynamics over time. However, the limited spatial and temporal resolution of this imaging modality can hinder the accurate assessment of complex hemodynamic phenomena. This thesis explores the application of Physics-Informed Neural Networks (PINNs) to enhance the resolution of 4D flow MRI data, thereby improving its clinical utility. PINNs are a class of neural networks that integrate physical laws into their training process. By embedding these physics equations, PINNs can discover the underlying physics of fluid dynamics to produce more …


Hyperspectral Image Classification Of Bacteria Using A Deep Convolutional Neural Network, Bruce S. Vogelsberg Jr 2024 Clemson University

Hyperspectral Image Classification Of Bacteria Using A Deep Convolutional Neural Network, Bruce S. Vogelsberg Jr

All Theses

Hyperspectral imaging is a non-invasive imaging method capable of collecting both spatial and spectral information. However, because of the large volume of data collected, much of it is redundant or not useful for classification. Deep learning is a subset of machine learning that uses artificial neurons in a multilayered structure to learn representations from data. One of the main advantages of deep learning is the powerful feature extraction capabilities, which allow the model to learn both high- and low-level features. Convolutional neural networks are a type of deep learning model that have alternating convolutional and pooling layers capable of extracting …


Fluid-Solid Coupled Analysis Of Biological Samples In A Flow Chamber Using Optical Coherence Tomography, Reece W. Fratus 2024 Clemson University

Fluid-Solid Coupled Analysis Of Biological Samples In A Flow Chamber Using Optical Coherence Tomography, Reece W. Fratus

All Dissertations

Forces from fluid flow on a tissue or cellular boundary can drive remodeling processes through mechanotransduction pathways. In most cases, the exact mechanisms are not understood, such as in marine biofilm development or vascular remodeling. To gain a better understanding of these interactions, the flow profile at a solid boundary and the mechanical changes of that solid can be coupled together to determine the impact of fluid flow on mechanical remodeling. To achieve this, optical coherence tomography (OCT) is used to image the fluid and solid simultaneously. Fluid seeded with particles can be imaged and run through a particle image …


Contribution Of Collagen Type I To The Mechanical Properties Of Myocardial Tissues At The Micron Level, Adam Baker 2024 Clemson University

Contribution Of Collagen Type I To The Mechanical Properties Of Myocardial Tissues At The Micron Level, Adam Baker

All Dissertations

Collagen is a critical component of the organization and one of the key factors contributing to the mechanical stability of the myocardium. Where cardiomyocytes actuate to contract the heart and deliver blood to the lungs and the entire body, the local collagen network must be able to support the mechanical needs of the heart by enhancing rigidity, reducing the mechanical responsibility of cells, and increasing compliance to add loading capacity during diastole. At an organ-wide level, this has been measured and modeled in many ways. At the tissue level, the mechanical properties have been evaluated using techniques such as bi-axial …


Segmentation And Classification Of Left Ventricular Abnormalities In Cardiac Mri Using Initial Point Prediction Based Deformable Model, Md. Asadur Rahman, Md. Al Noman, A. B. M. Aowlad Hossain 2024 Military Institute of Science and Technology

Segmentation And Classification Of Left Ventricular Abnormalities In Cardiac Mri Using Initial Point Prediction Based Deformable Model, Md. Asadur Rahman, Md. Al Noman, A. B. M. Aowlad Hossain

Future Computing and Informatics Journal

The shape of the left ventricle (LV) of a cardiac magnetic resonance image (CMRI) helps physicians to diagnose different cardiac abnormalities. The similarity of pixel intensity and shape of LV with neighbor tissues, the imprecision of boundaries, and the presence of noise are the challenges to accurate segmentation of LV. This paper contributes to the successful implementation of an automatic edge contouring method to segment LV area from CMRI and detect whether the ventricle belongs to abnormalities. This method proposes the regression-based artificial neural network to predict the possible initial position of the deformable edge-based active contour model for precise …


Preclinical Examination Of A Nerve Specific Fluorophore Using Ex Vivo Human Tissues, Logan Michael Bateman 2024 Dartmouth College

Preclinical Examination Of A Nerve Specific Fluorophore Using Ex Vivo Human Tissues, Logan Michael Bateman

Dartmouth College Master’s Theses

Fluorescence-guided surgery (FGS) is a nascent field which seeks to improve patient safety and surgical outcomes using fluorescent agents known as fluorophores. Fluorophores are molecules which upon excitation with a specific wavelength of light emit a photon of a specific wavelength which can be detected using a modified camera system. Creation and translation of a fluorophore for clinical use is a costly, laborious, and time intensive process. Only a handful of fluorophores have received FDA approval and they required multiple years of tightly regulated clinical trials. Prior to these first-in-human studies these agents are subject to a litany of preclinical …


Single-Molecule Orientation Imaging Reveals The Nano-Architecture Of Amyloid Fibrils Undergoing Growth And Decay, Brian Sun, Tianben Ding, Weiyan Zhou, Tara S. Porter, Matthew D. Lew 2024 Washington University in St. Louis

Single-Molecule Orientation Imaging Reveals The Nano-Architecture Of Amyloid Fibrils Undergoing Growth And Decay, Brian Sun, Tianben Ding, Weiyan Zhou, Tara S. Porter, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Amyloid-beta (Aβ42) aggregates are characteristic Alzheimer’s disease signatures, but probing how their nanoscale architectures influence their growth and decay remains challenging using current technologies. Here, we apply time-lapse single-molecule orientation-localization microscopy (SMOLM) to measure the orientations and rotational “wobble” of Nile blue (NB) molecules transiently binding to Aβ42 fibrils. We correlate fibril architectures measured by SMOLM with their growth and decay over the course of 5 to 20 min visualized by single-molecule localization microscopy (SMLM). We discover that stable Aβ42 fibrils tend to be well-ordered and signified by well-aligned NB orientations and small wobble. SMOLM also shows that increasing order …


Development Of A Two-Photon Imaging System, Jesseca Hollenbaugh 2024 Portland State University

Development Of A Two-Photon Imaging System, Jesseca Hollenbaugh

University Honors Theses

The objective of this project was to convert a Sarastro 2000 confocal laser scanning microscope (CLSM) into a system capable of far-field two-photon excitation (TPE) imaging for the use of the PSU Biology department. TPE microscopy operates on the ability of fluorophores to accept two photons each with half the energy of a desired transition in a single quantum event via a virtual energy state and then emit a higher energy photon upon relaxation. This is preferable to single-photon excitation (SPE) imaging due to lower photon imaging, causing less damage to delicate biological samples, as well as the inherent localization …


Data-Driven Insights Into Spatial Patterns And Disease Etiologies Of White Matter Hyperintensities, Sugandha Roy 2024 Washington University in St. Louis

Data-Driven Insights Into Spatial Patterns And Disease Etiologies Of White Matter Hyperintensities, Sugandha Roy

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we have applied Orthogonal Projective Non-Negative Matrix Factorization (opNMF) to identify spatial patterns of white matter hyperintensities (WMH) within UK Biobank's imaging data. Our selection criteria excluded subjects with a history of neurological, mental, and specific cerebrovascular conditions, allowing us to focus on WMH patterns in a healthy aging population. We have interrogated the association of location-specific WMHs with a variety of demographic, clinical, and genetic factors. Our multivariable regression analysis evaluates the strength and nature of the associations between these factors and WMH distribution. The analysis integrates variables such as age, sex, smoking habits, medication usage …


An Attention Lstm U-Net Model For Drosophila Melanogaster Heart Tube Segmentation, Xiangping Ouyang 2024 Washington University in St. Louis

An Attention Lstm U-Net Model For Drosophila Melanogaster Heart Tube Segmentation, Xiangping Ouyang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Machine learning is commonly used in biomedical image analysis, as it allows automated image segmentation and identification that minimizes the need for tedious human involvement. Drosophila melanogaster is often used as a cardiac disease model, where optical coherence microscopy (OCM) is used to image and analyze its beating dynamics. As OCM often generates a large volume of images, automated image segmentation is necessary to quantify the heart beating efficiently. Our most recent heart segmentation model, FlyNet 2.0+, is a fully convolutional LSTM U-Net model. However, the performance of the model diminishes in the presence of artifacts, such as image reflection …


Calcium Analysis Of Intercellular Communications Between Alpha Cells And Delta Cells Across The Pancreatic Islet, Shichao Gao 2024 Washington University in St. Louis

Calcium Analysis Of Intercellular Communications Between Alpha Cells And Delta Cells Across The Pancreatic Islet, Shichao Gao

McKelvey School of Engineering Graduate Student Theses & Dissertations

The intricate communication between different cell types within pancreatic islets plays a crucial role in regulating glucose homeostasis. Among these cellular interactions, the interplay between α cells (responsible for glucagon secretion) and δ cells (secreting somatostatin) is particularly intriguing due to the inhibitory effects of somatostatin on glucagon release. Understanding the intercellular interactions between α and δ cells may provide insights into the mechanisms underlying the coordinated regulation of blood glucose levels. In this study, we employed a multi-modal approach combining confocal imaging, image analysis, and correlation network analysis to investigate the spatial relationships and potential functional connections between α …


Structured Light Radial-View Endoscope Imaging Development For Evaluation Of Human Tissue, Xiyan Li 2024 Washington University in St. Louis

Structured Light Radial-View Endoscope Imaging Development For Evaluation Of Human Tissue, Xiyan Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we improved an existing structured light methodology to more accurately estimate tissue optical properties imaged in a single snapshot. The developed approach is a major enhancement of the traditional three-phase spatial frequency domain imaging system: It greatly simplifies the operational procedure while also maintaining high accuracy in optical property measurements .

Leveraging this improved approach, we have developed a low-cost, compact, and radial-view endoscope prototype. This prototype combines affordability with high functionality and a user-friendly design. To assess the performance and reliability of our endoscope, we conducted comprehensive evaluations involving tissue-mimicking phantoms, as well as ex vivo …


Evaluating Neuroimaging Modalities In The A/T/N Framework: Single And Combined Fdg-Pet And T1-Weighted Mri For Alzheimer’S Diagnosis, Peiwang Liu 2024 Washington University in St. Louis

Evaluating Neuroimaging Modalities In The A/T/N Framework: Single And Combined Fdg-Pet And T1-Weighted Mri For Alzheimer’S Diagnosis, Peiwang Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

With the escalating prevalence of dementia, particularly Alzheimer's Disease (AD), the need for early and precise diagnostic techniques is rising. This study delves into the comparative efficacy of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and T1-weighted Magnetic Resonance Imaging (MRI) in diagnosing AD, where the integration of multimodal models is becoming a trend. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we employed linear Support Vector Machines (SVM) to assess the diagnostic potential of these modalities, both individually and in combination, within the AD continuum. Our analysis, under the A/T/N framework's 'N' category, reveals that FDG-PET consistently outperforms T1w-MRI across …


Utilizing Spatial Transcriptomics To Compare Gene Expression In Volumetric Muscle Loss Injury Recovery, Colton Gattis 2024 University of Arkansas, Fayetteville

Utilizing Spatial Transcriptomics To Compare Gene Expression In Volumetric Muscle Loss Injury Recovery, Colton Gattis

Biomedical Engineering Undergraduate Honors Theses

Volumetric Muscle Loss (VML) injuries are known to disrupt the normal regenerative process via fibrosis leading to an extensive permanent loss of muscle function. The specific causation of this disruption remains to be defined; however, with new developments in transcriptomics, genetic trends can be identified across regions of tissue over time. This study follows VML injuries within the tibialis anterior of a mouse model for fifteen days after initial injury to attempt to identify expected transitions in healing. Genetic presence began to become more diversified as recovery progressed from four to fifteen days post injury with spatial clusters becoming globalized …


Advancements Of A Breast Tissue Marker And Localization System, Azrin Jamison 2024 Clemson University

Advancements Of A Breast Tissue Marker And Localization System, Azrin Jamison

All Theses

Breast cancer has become the most prominent cancer worldwide in women. Annual mammograms are encouraged for women of high risk to increase early detection allowing for lumpectomies rather than mastectomies to occur. Prior to a lumpectomy, a biopsy must be taken to determine if the tissue is cancerous, and a breast cancer biopsy marker (BBM) is left in the region of possible cancerous tissue. Wire localization has been the gold standard for localizing these BBMs. However, due to the reported patient discomfort and logistical inefficiencies faced by healthcare providers (HCP), non-wire localization solutions have been recently developed. This study aims …


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