Bioimaging and Biomedical Optics Commons^™

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 …

Microwave Imaging Technique For Breast Cancer Detection, Nure Alam Chowdhury

Theses and Dissertations

Breast cancer is a global problem, and it is inevitable to detect cancerous cells at early stages. In recent years, microwave imaging technology has been widely applied in biomedical applications for its non-ionizing radiation. In this study, we design a micro-strip patch antenna with an inverted T-type notch in the partial ground to detect tumor cells inside the human breast. The size of the current antenna is small enough (18 mm × 21 mm × 1.6 mm) to distribute around the breast phantom. The operating frequency has been observed from 6–14 GHz with a minimum return loss of −61.18 dB …

Multi-Magnetic Material Transcranial Magnetic Stimulation Coils Development And Electric Field Measurement & Modeling Using Machine Learning, Mohannad Tashli

Theses and Dissertations

Transcranial Magnetic Stimulation (TMS) is a safe, effective, and non-invasive therapy for treating several psychiatric and neurological disorders. TMS is Food and Drug Administration (FDA) approved treatment and is commonly applied to patients who do not respond to medications for the treatment of clinical depression, smoking cessation, obsessive-compulsive disorder and migraine. Recently, there has been an increase in the development of electromagnetic neuromodulation techniques targeted at enhancing the effectiveness of TMS devices for the treatment of mental diseases. In TMS stimulation, focality is an important factor which determines the specificity of the pulses induced in different brain tissues. The electromagnetic …

An Improved Saliency Map With Trustworthiness For Localizing Abnormalities In Medical Imaging, Nolan C. Skelly

Theses and Dissertations

Saliency maps are a widely used methodology to make deep learning models more interpretable. They provide post-hoc explanations through identification of the most pertinent areas of an input medical image. These techniques have been assessed based on 1) localization utility, 2) sensitivity to model weight randomization, 3) repeatability, and 4) reproducibility. Ten saliency map techniques will be tested, Grad, Smooth Grad, Integrated Gradients, Smooth Integrated Gradients, XRAI, Grad-CAM, Guided Backpropagation, Guided GradCAM, GradCAM++, and ScoreCAM. The neural networks used to predict and read medical information require a reliable solution to provide medical practitioners intelligible results. Using the information of two, …

Deep Learning And Generative Ai Approaches For Automated Diagnosis And Personalized Treatment: Bridging Machine Learning, Medicine, And Biomechanics In Predicting Tissue Mechanics And Biomaterial Properties., Yasin Shokrollahi

Theses and Dissertations

Machine learning, particularly deep neural networks, has demonstrated significant potential in predicting high-dimensional tasks across various domains. This work encompasses a detailed review of Generative AI in healthcare and three studies integrating machine learning with finite element analysis for predicting biomechanical behaviors and properties. Initially, we provide a comprehensive overview of Generative AI applications in healthcare, focusing on Transformers and Denoising Diffusion models and suggesting potential research avenues to address existing challenges.

Subsequently, we addressed soccer-related ocular injuries by combining finite element analysis and machine learning to predict retinal mechanics following a soccer ball hit rapidly. The prediction errors are …

Efficient Scopeformer: Towards Scalable And Rich Feature Extraction For Intracranial Hemorrhage Detection Using Hybrid Convolution And Vision Transformer Networks, Yassine Barhoumi

Theses and Dissertations

The field of medical imaging has seen significant advancements through the use of artificial intelligence (AI) techniques. The success of deep learning models in this area has led to the need for further research. This study aims to explore the use of various deep learning algorithms and emerging modeling techniques to improve training paradigms in medical imaging. Convolutional neural networks (CNNs) are the go-to architecture for computer vision problems, but they have limitations in mapping long-term dependencies within images. To address these limitations, the study explores the use of techniques such as global average pooling and self-attention mechanisms. Additionally, the …

Advanced Modeling And Innovative Transcranial Magnetic Stimulation Coil Designs For The Treatment Of Neurological Disorders, Mohannad Tashli

Theses and Dissertations

Transcranial magnetic stimulation (TMS) is a safe, effective and non-invasive treatment for several mental and psychiatric disorders. TMS is an FDA approved treatment and is commonly applied to patients who do not respond to medications for the treatment of clinical depression, smoking cessation, obsessive-compulsive disorder and migraine. Recently, there has been an increase in the development of electromagnetic neuromodulation techniques targeted at enhancing the effectiveness of TMS devices for the treatment of mental diseases. In TMS stimulation, focality is an important factor which determines the specificity of the pulses induced in different brain tissues. The electromagnetic pulses must be confined …

Imaging Potential In Saturation Recovery Methods For Sarcoidosis Patients With Medical Devices, Samantha Zhao

Theses and Dissertations

Cardiovascular magnetic resonance (CMR) imaging is a preferred imaging methodology due to its lack of ionizing radiation and ability to detect myocardial inflammation and fibrosis using quantitative T1 mapping techniques. Cardiac sarcoidosis (CS) is characterized as the formation of granulomas in the myocardium. Current methods for detection include measuring non-cardiac specific C-reactive protein (CRP) levels, or PET imaging, which uses ionizing radiation, therefore CMR would make an ideal imaging option. However, many CS patients have implanted cardiac devices which can cause degradation in image. The modified Look-Locker inversion recovery (MOLLI) method is widely used in quantitative T1 mapping with high …

Nanoscale Material Interaction With Multicellular 3d Cancer Culture, Emilie Darrigues

Theses and Dissertations

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, it is difficult to diagnose, often recurs, has high resistance to chemotherapies, and can be marked by advanced metastatic stages. There is an urgent need to fill the knowledge on nanoparticle penetration, diffusion, and cellular interaction in the context of adaptive PDAC tumor microenvironment to allow the development of new imaging and therapeutic supports. Traditionally, cancer-treating nanoparticles have been engineered and tested on 2D cell cultures, but several studies indicate that this in vitro model does not mimic tumor features closely enough. In contrast, 3D culture models offer …

Higher Tensile Forces Across Cellular Junctions And An Intact Nuclear Linc Complex Is Required For Epithelial Function And Stability, Fnu Vani Narayanan

Theses and Dissertations

Recent advances in three-dimensional (3D) cell culture systems have provided key insights into the understanding of biochemical and physiological states of native tissue. A significant progress in the field of mechanobiology involves measuring cellular traction forces in a more native 3D environment. However, the effects of mechanical forces exerted across cellular junctions and the nuclear LINC complex, in an organized 3D system has not been investigated thus far. Epithelial cells spontaneously form acini (also known as cysts or spheroids) with a single, fluid-filled central lumen, when grown in 3D matrices. The size of the lumen is dependent on apical secretion …

Automatic Hip Analysis Suite, Nathan J. Veilleux

Theses and Dissertations

Image recognition and computer vision are becoming increasingly useful for diagnostic and surgical planning purposes. Analyses of patient morphology can be performed much more quickly and reliably with algorithmic assistance. Traditional measurements of the hip involve visual inspection of patient radiographs or hand calculation with software assistance. In the most extreme cases, estimates of bone orientation are made via palpation of a patient’s hip. There is the possibility for significant improvements in reliability if measurements can be made in the absence of human interpretation. As many of these techniques require CT scans as a prerequisite, all of the necessary information …

Development And Validation Of A Novel Resonant Energy Transfer (Fret) Biosensor To Measure Tensile Forces At The Linc Complex In Live Cells, Paul Arsenovic

Theses and Dissertations

There is a large body of evidence supporting the theory that cell physiology largely depends on the mechanical properties of its surroundings or micro-environment. More recently studies have shown that changes to intra-cellular mechanical properties can also have a meaningful impact on cell function and in some cases lead to the progression of ailments or disease. For example, small changes to the protein sequence of a structural nuclear envelope protein called lamin-A is known to cause a variety of neurological and musculoskeletal diseases referred to as laminopathies. Currently, there is little incite into how these mutations lead to disease progression …

Raman Spectroscopy As A Tool For Single Circulating Tumor Cell (Ctc) Detection And Imaging, Zeid A. Nima

Theses and Dissertations

Breast cancer is the most common type of cancers in the United States. It is imperative that a quick and reliable method for the early detection of circulating tumor cells (CTCs) be identified and tested. In this research several new detection and imaging techniques based on using Raman spectroscopy have been invented. Raman active nano-complex agents based on single-walled carbon nanotubes (SWCNTs) were prepared and used for the swift and specific detection of breast cancer cells. SWCNTs are functionalized with the anti-epithelial cell adhesion molecule (anti-EpCAM) antibody, were able to detect CTCs within 30 min and discriminate few CTCs among …

Femtosecond Laser Beam Propagation Through Corneal Tissue: Evaluation Of Therapeutic Laser-Stimulated Second And Third-Harmonic Generation, William R. Calhoun Iii

Theses and Dissertations

One of the most recent advancements in laser technology is the development of ultrashort pulsed femtosecond lasers (FSLs). FSLs are improving many fields due to their unique extreme precision, low energy and ablation characteristics. In the area of laser medicine, ophthalmic surgeries have seen very promising developments. Some of the most commonly performed surgical operations in the world, including laser-assisted in-situ keratomileusis (LASIK), lens replacement (cataract surgery), and keratoplasty (cornea transplant), now employ FSLs for their unique abilities that lead to improved clinical outcome and patient satisfaction.

The application of FSLs in medical therapeutics is a recent development, and although …

Quantitative Object Reconstruction Using Abel Transform Tomography And Mixed Variable Optimization, Kevin R. O'Reilly

Theses and Dissertations

Researchers at the Los Alamos National Laboratory (LANL) are interested in quantitatively reconstructing an object using Abel transform x-ray tomography. Specifically, they obtain a radiograph by x-raying an object and attempt to quantitatively determine the number and types of materials and the thicknesses of each material layer. Their current methodologies either fail to provide a quantitative description of the object or are generally too slow to be useful in practice. As an alternative, the problem is modeled here as a mixed variable programming (MVP) problem, in which some variables are nonnumeric and for which no derivative information is available. The …

Using Kriging To Interpolate Spatially Distributed Volumetric Medical Data, Stephen M. Matechik

Theses and Dissertations

Routine cases in diagnostic radiology require the interpolation of volumetric medical imaging data sets. Inaccurate renditions of interpolated volumes can lead to the misdiagnosis of a patient's condition. It is therefore essential that interpolated modality space estimates accurately portray patient space. Kriging is investigated in this research to interpolate medical imaging volumes. Kriging requires data to be spatially distributed. Therefore, magnetic resonance imaging (MRI) data is shown to exhibit spatially regionalized characteristics such that it can be modeled using regionalized variables and subsequently be interpolated using kriging. A comprehensive, automated, three-dimensional structural analysis of the MRI data is accomplished to …

Evaluation Of Segmentation For Bone Structures In 3d Rendering Of Ultrasound Residual Limb Images, Min C. Baker

Theses and Dissertations

Prosthetists today widely practice manual socket fitting, which produces subjective, inconsistent results. To address this problem, the Computerized Anthropometry Research and Design (CARD) Laboratory is developing a computer-aided socket design system that acquires ultrasound datasets of an amputee's residual limb, creates a 3D model, and helps identify load- bearing and pressure-relief areas. This research project focuses on providing 3D visualization of a residual limb to support the CARD Laboratory's efforts. Creating the 3D model of the skin and two bone contours requires two major steps: segmentation to identify the objects of interest and a surface tracking algorithm to generate the …

Clustered Microcalcification Detection Using Optimized Difference Of Gaussians, Edward M. Ochoa

Theses and Dissertations

The objective of this thesis is to design an automated microcalcification detection system to be used as an aid in radiologic mammogram interpretation. This research proposes the following methodology for clustered microcalcification detection. First, preprocess the digitized film mammogram to reduce digitization noise. Second, spatially filter the image with a difference of Gaussians (DoG) kernel. To detect potential microcalcifications, segment the filtered image using global and local thresholding. Next, cluster and index these detections into regions of interest (ROIs). Identify ROIs on the digitized image (or hardcopy printout) for final radiologic diagnosis.

Pulse Coupled Neural Networks For The Segmentation Of Magnetic Resonance Brain Images, Shane L. Abrahamson

Theses and Dissertations

This research develops an automated method for segmenting Magnetic Resonance (MR) brain images based on Pulse Coupled Neural Networks (PCNN). MR brain image segmentation has proven difficult, primarily due to scanning artifacts such as interscan and intrascan intensity inhomogeneities. The method developed and presented here uses a PCNN to both filter and segment MR brain images. The technique begins by preprocessing images with a PCNN filter to reduce scanning artifacts. Images are then contrast enhanced via histogram equalization. Finally, a PCNN is used to segment the images to arrive at the final result. Modifications to the original PCNN model are …

Detection Of Clustered Microcalcifications Using Wavelets, Donald A. Mccandless

Theses and Dissertations

An automated method for detecting microcalcification clusters is presented. The algorithm begins with a digitized mammogram and outputs the center coordinates of regions of interest (ROIs) that contain microcalcification clusters. The method presented uses a 12-tap Least Asymmetric Daubechies (LAD12) wavelet in a tree structured filter bank to increase the signal to noise level of microcalcifications. The signal to noise level gain achieved by the filtering allows subsequent thresholding to eliminate on average 90% of the image from further consideration without eliminating actual microcalcifications 95% of the time. A novel approach to isolating individual calcifications from background tissue through non-stationary …

Computer-Aided Diagnosis Of Mammographic Masses, William E. Polakowski

Theses and Dissertations

A new Model-Based Vision algorithm was developed to find possibly cancerous regions of interest (ROIs) in digitized mammograms and to correctly identify the malignant masses. This work has shown a sensitivity of 92 percent for locating malignant ROIs. The database contained 272 images (12 bit, 1OO microns) with 36 malignant and 53 benign mass images. Of the 53 biopsied benign cases, 74 percent were correctly classified. The Focus of Attention (segmentation) Module algorithm used a physiologically motivated Difference of Gaussians (DoG) filter to highlight mass-like regions in the mammogram. The Index Module labeled the regions by their hypothesized class: large …

Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk

Theses and Dissertations

A comparative study of texture measures for the classification of breast tissue is presented. The texture features investigated include Angular Second Moments, Power Spectrum Analysis and a novel feature, Laws Energy Ratios. The texture study was accomplished as part of the development of a Model Based Vision (MBV) system for the automatic detection of microcalcifications. An overview of the Microcalcification Detection System is presented, which applies image differencing techniques, feature selection methods, and neural networks for locating microcalcification clusters in mammograms. The Power Spectrum Analysis feature set had the best overall performance with an 83% Probability of Detection and an …

Three Dimensional Localization Of Lesions From Digitized Mammograms, Amy L. Magnus

Theses and Dissertations

This thesis describes new algorithms to localize regions-of-interests (ROIs) three dimensionally from a pair of digitized mammograms. This work is intended to add a layer of sophistication to computer aided diagnosis by putting to use the fixed and measurable parameters of mammographic imaging. The fixed parameters are the source to film orientation and the podium-image distance. Measurable parameters are the rotation angle of the x-ray tube from the horizontal and the compression depth (the distance from compression paddle to contact podium distance) at the time of imaging. As an additional benefit, three dimensional localization algorithms alleviate the confusion radiologists may …

Evaluation Of Scalar Value Estimation Techniques For 3d Medical Imaging, Rob W. Parrott

Theses and Dissertations

Scalar value estimation in 3D medical imaging increases data resolution for enhanced renditions and corrects inaccurate surface formations. Accurate estimations are vital because clinical assessment is often aided by examination of 3D medical images. This thesis explores different estimation techniques and introduces the geostatistical estimation technique called kriging to the field of 3D imaging. Kriging theory claims to be the optimal estimator-- better than the standard deterministic methods commonly used. The techniques investigated are linear interpolation, trilinear interpolation, tricubic interpolation, and kriging. This research investigates scalar value estimation in the volume pre-processing operation of slice interpolation and in a surface …