Bioimaging and Biomedical Optics Commons^™

Mri-Based Estimation Of The Hip Joint Center In Infants Using Two Sphere-Fitting Methods, Victoria Melendez

Discovery Day - Daytona Beach

Accurate estimation of the hip joint center (HJC) is critical for biomechanical modeling and clinical assessment. Common methods include predictive methods (e.g., regression equations) and functional methods such as sphere-fitting. In infants, femoral head-based methods are often limited due to incomplete ossification of the anatomy and poor visualization in computed tomography (CT) images. This study evaluates an alternative approach using MRI-based sphere fitting of the ossified acetabular rim, comparing its accuracy to traditional femoral head-based methods. MRI scans of three male infants (ages 10.7- 12.7 months) were used to manually place landmarks on the ossified acetabulum and the cartilaginous boundary …

Vergence Task-Based Neural Pathways With Binocularly Normal Vision And Comorbid Persistent Post-Concussive Symptoms -Convergence Insufficiency, Ayushi Sangoi

Dissertations

Binocular dysfunctions are more prevalent in the persistent post-concussive symptoms (PPCS) population than in the general population. The most prevalent binocular disorder is convergence insufficiency (CI), affecting 3-17% of the general population and up to 10 times as many people with PPCS. CI makes it difficult to fuse or maintain fusion on targets at near, and its symptoms include double or blurry vision and headaches when performing close-range tasks such as reading, which can exacerbate PPCS symptoms. Given controversy over the subjectivity and effectiveness of diagnostic tools and symptom surveys for both PPCS and CI, understanding why CI has high …

Characterizing Stiffness Dynamics Of Normal And Malignant Breast Spheroids Using Brillouin Microscopy, Razanne Rafat Zaghloul, Karlin Hilai, Chenjun Shi, Jitao Zhang

Medical Student Research Symposium

Background: Breast cancer progression and metastasis are closely linked to alterations in the mechanical properties of tumor cells and their microenvironment. Softer, more deformable cells are often associated with higher metastatic potential. While atomic force microscopy (AFM) is the current gold standard for mechanical characterization, it is limited to surface measurements and can damage 3D cultures. It remains unclear how the mechanical properties evolve over time in normal versus malignant spheroids. This study utilizes Brillouin light-scattering microscopy, a non-contact and label-free optical technique, to assess stiffness changes in normal and malignant breast epithelial spheroids over time. Understanding these mechanical signatures …

Spectral Characterization Of Colorectal Cancer Using Excitation-Scanning Hyperspectral Imaging, Natalie Hadad

Honors Theses

Colorectal cancer is one of the most common and deadly cancers worldwide, with a lifetime risk of approximately one in twenty-three for men and one in twenty-five for women. Although early detection significantly improves survival, current diagnostic approaches such as tissue biopsy are invasive, reliant on subjective interpretation, have extended turnaround times, and risk missing flat or depressed lesions that are more difficult to detect than raised polyps. These limitations highlight the need for objective, minimally invasive technologies capable of detecting early tissue changes. This study investigates excitation-scanning hyperspectral imaging (Ex-HSI) as a label-free optical approach for identifying colorectal cancer–associated …

Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem

Dartmouth College Ph.D Dissertations

Surgical resection remains to be the cornerstone of treatment for most solid tumors, where the primary objective is to remove all visible and microscopic disease. However, the extent of tumor resection is inherently limited by the surgeon’s ability to distinguish tumor from normal tissue, intraoperatively. As a result, positive surgical margins (PSM), where residual tumor remains after surgery, are a common occurrence and are associated with increased recurrence, need for adjuvant therapies, dismal patient outcomes, and high healthcare costs.

Fluorescence guided surgery (FGS) has emerged as a promising technique to enhance intraoperative visualization of tumors and may help reduce the …

Mechanical Characterization And Modeling Of Rat Myocardia Under The Influence Of Epirubicin, Abdallah Mahmoud Alkhaiyat

Theses and Dissertations

Cancer remains a predominant health challenge that is responsible for a significant portion of global morbidity and mortality. Epirubicin (EPI), a chemotherapeutic anti-cancer drug, has shown remarkable efficacy in combating various malignancies. However, it is known to have undesirable side effects on the heart, collectively referred to as cardiotoxicity. This research investigates the adverse effects of chemotherapy on cardiac contractility through an in vitro examination of the mechanics of healthy and infarcted animal heart tissues. Electrically stimulated slices of rat ventricular tissue were tested using an isometric force measurement tissue bath. The tissue slices were subjected to uniaxial stretching, allowing …

Influence Of Motion Artifacts On Instantaneous Frequency Based Heart Rate Variability Of Arterial Pulse Signals Measured By A Tactile Sensor: An Analytical Study, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Objective: Heart rate variability (HRV), quantified via the instantaneous frequency (IF) of arterial pulse signals, is a key indicator of cardiovascular (CV) regulation. This study presents a theoretical and experimental investigation of how motion artifacts (MA) influence IF-and thus HRVmeasured with a tactile sensor, emphasizing underlying mechanisms rather than population-level validation. Approach: Building on a previously developed single-degree-of-freedom (SDOF) model of the tissue-contact-sensor (TCS) stack between the sensor and the artery, MA is represented as low-frequency baseline drift and time-varying system parameters (TVSP) of the TCS stack. Analytical expressions quantify the effect of MA on the IF of each harmonic …

Fill The Void - An Introductory Guide For Learning Medical Imaging, Reid Faith, Peter Gahan, Adam Trusty, Aleksandr Zyskin, Chukwuka Ukekwe, Denise Nchinda, Amanda K. Burbage, Alberto E. Musto

EVMS School of Health Professions Faculty Publications

No standardized, comprehensive approach for radiological image interpretation exists among medical schools in the United States of America. In order to rectify this, we outline a model aimed to help improve how medical imaging can be taught in medical schools. The VOID (Visualization, Orientation/Observation, Identification, Description) guide is a proposed universal, stepwise approach to medical image identification, interpretation, and communication. This structured guideline is aimed at building a foundation for students in early medical education. The VOID was applied to CT (Computed Tomography), MRI (Magnetic Resonance Imaging), and x-ray modalities as integrated sessions for medical students during human anatomy laboratory. …

Adversarial Robustness In Biomedical Time-Series Models, Rohan Tiwari

Bioengineering Theses

This study investigates adversarial vulnerabilities in deep learning models for biomedical time-series classification across two clinically important modalities: electrocardiography (ECG) and electroencephalography (EEG). Using the MIT-BIH Arrhythmia and CHB-MIT seizure datasets, I evaluate time-domain attacks (FGSM, PGD), Fourier-domain constrained attacks, and learned spectral perturbations designed to reveal modality-specific sensitivity patterns. Across both tasks, a consistent trend emerges low-frequency components (0–5 Hz) constitute a dominant axis of adversarial vulnerability, with perturbations in this range producing the steepest degradation in classification performance. In ECG models, protecting the physiologically relevant QRS band (5–20 Hz) significantly improves robustness, whereas EEG models remain highly sensitive …

Sex-Dependent Differences In Cardiac Function And Strain In Doxorubicin-Induced Cardiomyopathy, Anna J. A. Webb, Bea O. Cabot, Aasish Chowdary, Wilhelm S. Smith, Benjamin Zeidler, Cortland H. Johns, Craig J. Goergen

Discovery Undergraduate Interdisciplinary Research Internship

Doxorubicin is a chemotherapeutic agent used to treat many types of cancer. While effective, doxorubicin can cause cardiomyopathy, a disease affecting the heart muscle. Although the effects of doxorubicin on the heart are well studied, the mechanisms leading to cardiomyopathy are not well understood. Previous studies have used murine models to study the cardiotoxicity of doxorubicin. These reports showed that cardiac dysfunction is more pronounced in male compared to female mice. The goal of this study is to further evaluate sex differences in doxorubicin induced cardiomyopathy using 4-dimensional strain mapping techniques. In this study, both female and male C57Bl/6J mice …

Advancing Novel Contrast Agents For Applications In Fluorescence-Guided Neurosurgery Using Fluorescence Cryotomography, Augustino Vittorio Scorzo

Dartmouth College Ph.D Dissertations

Fluorescence guided surgery (FGS) is an emerging surgical technique that aims to help surgeons identify tissue types to assist in surgical decision making - ideally providing “cut-by-color” guidance. A primary application for this approach is the identification of tumor tissue to achieve more accurate and complete tumor removal while simultaneously minimizing damage to surrounding normal tissue. The cornerstone of tumor visualization for FGS is the administration of fluorescent contrast agents, or in some cases metabolic precursors, designed to accumulate specifically in tumor tissue, and a wide range of agents that use different targeting mechanisms are currently under investigation. Although these …

Acoustic And Hemodynamic Analysis Of Phantoms: Roughness And Flow Dynamics, Ethan Erik Olof Sundberg

Master's Theses

The purpose of this study was to determine whether different vascular phantoms, with and without a surrogate arm, could serve as effective analogs to the human brachial artery for assessing endothelial dysfunction, an early indicator of cardiovascular disease, particularly atherosclerosis. Atherosclerosis is characterized by plaque buildup and endothelial damage, which precede more severe clinical events and are often detectable through changes in vascular function. A 40” water tower was used to simulate diastolic pressure, enabling water flow through each phantom. Strain gauge pressure transducers were placed at both ends of the phantoms to measure pressure drop, while a microphone captured …

Development Of A Light-Based Platform To Assess Cervical Mucus Barrier Function And Physical Mucus Properties, Elizabeth J. Buzbee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Preterm birth is the leading cause of neonatal morbidity and mortality worldwide, yet current clinical tools for predicting its risk lack specificity and reliability. Cervical mucus plays a crucial role in maintaining pregnancy by forming a barrier that protects the uterus against infection. This study investigates the use of laser speckle rheology as a noninvasive technique to assess cervical mucus biomechanics. Synthetic cervical mucus was fabricated at varying hydration levels and tested using a conventional rheometer that confirmed that the mechanical properties of the synthetic mucus samples were representative of physiological cervical mucus. These results were compared to the complex …

Towards The Performance Characterization Of A Robotic Multimodal Diagnostic Imaging System, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Nikolaos Michailidis, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Sean Starling, Christian Ruberg

Publications and Research

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal …

Multimodal Ai-Driven Biomarker For Early Detection Of Cancer Cachexia, Sabeen Ahmed

USF Tampa Graduate Theses and Dissertations

Cancer cachexia is a metabolic syndrome characterized by substantial skeletal muscle loss, impacting cancer patients' survival and quality of life. Despite its clinical significance, early detection remains a challenge due to the lack of standardized diagnostic criteria and the reliance on indirect markers. This work presents an AI-driven approach to enhance cachexia detection and monitoring by integrating multiple deep learning methodologies. We explore transformer architectures for time-series analysis to model sequential medical data, enabling disease prediction and progression modeling. To ensure robust and reliable decision-making in clinical settings, we explore Bayesian deep neural networks for uncertainty estimation. Additionally, we introduce …

Unified Adaptive Cross-Attention Multimodal Network, Mahesh Sunuwar

Shelby Hall Graduate Research Forum Posters

Accurately diagnosing appendicitis remains a significant challenge in emergency medicine due to its varied clinical presentation and overlap with other abdominal conditions. Existing diagnostic models often rely on unimodal data, such as computed tomography (CT) images or clinical notes, limiting their ability to capture the full complexity of patient information. This study proposes a novel multimodal framework, a Unified Adaptive Cross-Attention Multimodal Framework (u-ACM), that integrates CT images and clinical notes using hybrid fusion strategies to improve diagnostic accuracy for appendicitis. The u-ACM leverages adaptive contextual filtering to dynamically remove irrelevant features, crossattention mechanisms to align features between modalities, and …

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Multimodal Imaging Of Protein-Based Biomaterials For Delivering Chemo-Agent Cargo For Glioblastoma Treatment In A Murine Model, Orin Mishkit

Dissertations and Theses

Protein-based self-assembling biomaterials, known as Thermo-Responsive Assembled Proteins (TRAP), present meaningful potential as drug delivery carriers. These materials enable the controlled, slow release of poorly soluble chemotherapeutic agents, such as doxorubicin (Dox), while potentially reducing systemic off-target effects. In collaboration with multiple NYU labs, this study evaluated the efficacy of two TRAP variants—TRAP and F-TRAP—as drug delivery carriers in a xenograft mouse model of glioblastoma multiforme (GBM).

The primary objective was to compare the effectiveness of TRAP-loaded Dox (TRAP-DOX) to free Dox in achieving tumor extravasation and accumulation, facilitating sustained drug release. We hypothesized that the leaky vasculature of GBM …

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

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 …

Cochlear Electrode Insertion Training Model, Sarah Powell, Kaelyn E. Kraley, Nathan J. Smith

Williams Honors College, Honors Research Projects

Cochlear implant surgery is a delicate procedure performed by Otolaryngologists (ENTs) to implant an electronic device into the inner ear to provide a sense of sound for people who are profoundly deaf or hard of hearing. The current practices of training involve cadavers and 3D-printed models. Cadavers are commonly used but are expensive, single-use, and do not provide visual and haptic feedback, which are essential for medical students. 3D printed models are less commonly used and are hard to fabricate and not as realistic. If medical students are not properly trained for this delicate procedure, then risks are significantly increased …

Deep Learning-Assisted Diagnostic System: Apices And Odontogenic Sinus Floor Level Analysis In Dental Panoramic Radiographs, Pei Yi Wu, Yuan-Jin Lin, Yu-Jen Chang, Sung-Tsun Wei, Chiung An Chen, Kuo-Chen Li, Wei-Chen Tu, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Odontogenic sinusitis is a type of sinusitis caused by apical lesions of teeth near the maxillary sinus floor. Its clinical symptoms are highly like other types of sinusitis, often leading to misdiagnosis as general sinusitis by dentists in the early stages. This misdiagnosis delays treatment and may be accompanied by toothache. Therefore, using artificial intelligence to assist dentists in accurately diagnosing odontogenic sinusitis is crucial. This study introduces an innovative odontogenic sinusitis image processing technique, which is fused with common contrast limited adaptive histogram equalization, Min-Max normalization, and the RGB mapping method. Moreover, this study combined various deep learning models …

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 …

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 …

Nanoparticles For Applications In Specific Diagnostics And Precision Medicine, Naxhije Berisha

Dissertations, Theses, and Capstone Projects

Heterogeneity is common in the expression of cancer and treatment response. Precision medicine enables healthcare providers to tailor medical care to an individual's distinct genetic and environmental makeup. This customization has the potential to result in more efficient treatments while minimizing side effects. We believe that by studying the interface of nanotechnology and cancer medicine we can elucidate innovative solutions that address the challenges of disease heterogeneity. This includes advancements in drug delivery, formulations development, and diagnostic sensing. We highlight three studies that use nanotechnology for applications in precision medicine. In Chapter 2, we highlight design optimization of drug formulations …

Plasma Protein Signatures Of Adult Asthma, Gordon J. Smilnak, Yura Lee, Abhijnan Chattopadhyay, Annah B. Wyss, Julie D. White, Sinjini Sikdar, Jianping Jin, Andrew J. Grant, Alison A. Motsinger-Reif, Jian-Liang Li, Mikyeong Lee, Bing Yu, Stephanie J. London

Mathematics & Statistics Faculty Publications

Background: Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma.

Methods: Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with …

4d Epr Oximetry Imaging For 4d Bioprinting And Tissue Engineering, Sajad Sarvari

Graduate Theses, Dissertations, and Problem Reports (ETD)

Bioprinting, akin to 3D printing, employs cell-laden hydrogels such as GelMA (Gelatine Methacrylate) and Alginate instead of plastic or resin to create biological structures. The printing process followed by subsequent tissue maturation is known as 4D bioprinting, where the fourth dimension is time. Ensuring adequate and consistent oxygen, O2, supply within 3D bioprint volume over the entire maturation period process is crucial, as even transient hypoxia can impact cellular behavior and phenotypes. However, printing of fully developed vasculature remains an unresolved technical challenge. Several approaches to chemically (peroxides) or biologically (photosynthesis) generate oxygen during bioprint maturation have been proposed. However, …

Aggregation-Induced Emission Probe For Alzheimer's Detection And Treatment Screening, Gemini Ramlo

Williams Honors College, Honors Research Projects

The proposed project is to research if ROF-2, an aggregation-induced emitter, can be used to screen medications for Alzheimer's Disease and to accurately detect this disease, along with its progression. This will be done through multiple incubation periods using different identifiers that have already been solidified within Alzheimer's research to prove its ability and accuracy within screening and detection regarding this disease.

Unlv Title Iii Aanapisi & Mcnair Scholars Institute Research Journal 2024, Jesica Godinez-Paredes, Kian Hassankhan, Apia Hickman, Robin Ruth Kee, Kevin Ayala Pineda, Briana Melendez, Kalli Ramos, Saturn L. Reyes, Fabian Leija, Selena Pepe, Silva Topchyan, Celeste Ainsley, Mayra Arzate, Jessica Balistreri, Zantana Ephrem, Mirella Jasso, Karl Panou, Nichole Pelaez, Miklo Alcala, Akshay Dave, Mey Mey Heng, Michael Finkle, Janessa Montenegro, Reynafe Naol Aniga, Victor Mejia, Angelica G. Diaz, Anayeli Flores-Garibay, Kari Lee Joe Goold, Samantha Hernandez, Lianelys Cabrera Martinez, Caitlin Reynolds, Kimberly N. Usbeck, Abdulrahman Alahdal, Angelica Diaz, Willaine Mae Kahano, Raquel Jackson, Cecia Ruiz-Hernandez, Kers Ung-Watson, Yessenia Henriquez, Vanessa Marie Booth, Alexia Brown, Darlyn Magana, Bianca Navarro, Nicholas Pereira, Gia Renemae Calip, Lucky Heng, Ralph Sagun, Lucas Abreu, Alexandra Maria Acosta, Tristan Benally, Cosset Hernandez Pena, Adrian Montenegro, Cierra Paaaina-Daquioag, Nicole Torosian, Tracy Fuentes, Julissa Martinez, Medina Mcallister, Michal Newhouse-Van Vlerin, Tiria Carr, Nima Abkenar, Isabella Aceituno, Yuhan Bi, Victoria Campos, Melika Cummings, Zachary J. Johnigan, Alexis Sotolongo-Marin

McNair Journal

Journal articles based on research conducted by undergraduate students in the AANAPISI, LSAMP, and McNair Scholars Program.

Table of Contents

About AANAPISI

Dr. Chris Heavey, Interim President

Dr. Keith Rogers, Vice President for Student Affairs

Ms. Zhanna Aronov, Associate Vice President for Retention & Outreach

Don't Fear The Artificial Intelligence: A Systematic Review Of Machine Learning For Prostate Cancer Detection In Pathology, Aaryn Frewing, Alexander B. Gibson, Richard Robertson, Paul Urie, Dennis Della Corte

Faculty Publications

The adoption of whole slide image (WSI) scanners in clinical practice was accelerated by US Food and Drug Administration approval in 2017, which allowed primary pathologic diagnoses to be made on scanned images. Images in the digital domain allow the application of pathology artificial intelligence (AI), including clinical decision support with algorithms performing specific diagnoses.1,2 These algorithms, if trained properly, could go beyond the ability of human observation to detect and quantify features that are not recognizable by human perception.1,3,4