Bioimaging and Biomedical Optics Commons^™

Diagnostic Performance Of Receptor-Specific Surgical Specimen Staining Correlates With Receptor Expression Level, Jasmin M. Schaefer, Connor W. Barth, Scott C. Davis, Summer L. Gibbs

Dartmouth Scholarship

Intraoperative margin assessment is imperative to cancer cure but is a continued challenge to successful surgery. Breast conserving surgery is a relevant example, where a cosmetically improved outcome is gained over mastectomy, but re-excision is required in >25  %   of cases due to positive or closely involved margins. Clinical translation of margin assessment modalities that must directly contact the patient or required administered contrast agents are time consuming and costly to move from bench to bedside. Tumor resections provide a unique surgical opportunity to deploy margin assessment technologies including contrast agents on the resected tissues, substantially shortening the path to …

Ensuring Scientific Publishing Credibility In Translational Biomedical Optics., Brian W. Pogue

Dartmouth Scholarship

Optics has consistently been the largest singular technology sector used in medicine, and major advances in biomedical optics are documented daily in peer-reviewed publications. However, the academic stature of this field can be damaged by weaknesses in scientific publishing, where a “credibility crisis” has emerged as a popularized and increasingly studied dialogue. While there are still relatively few overt cases of fraud or erroneous research, more insidious aspects are seen in papers with results that have either low statistical power, selective reporting of observations, or data or computer codes that cannot be independently verified. Interestingly, the same solutions that improve …

3d Microwave Tomography Using The Soft Prior Regularization Technique: Evaluation In Anatomically-Realistic Mri-Derived Numerical Breast Phantoms, Amir H. Golnabi, Paul M. Meaney, Shireen D. Geimer, Keith D. Paulsen

Department of Mathematics Faculty Scholarship and Creative Works

Objective: Fusion of magnetic resonance imaging (MRI) breast images with microwave tomography is accomplished through a soft prior technique, which incorporates spatial information (from MRI), i.e. accurate boundary location of different regions of interest, into the regularization process of the microwave image reconstruction algorithm. Methods: Numerical experiments were completed on a set of 3D breast geometries derived from MR breast data with different parenchymal densities, as well as a simulated tumor to evaluate performance over a range of breast shapes, sizes and property distributions. Results: When the soft prior regularization technique was applied, both permittivity and conductivity relative root mean …

Abso2luteu-Net: Tissue Oxygenation Calculation Using Photoacoustic Imaging And Convolutional Neural Networks, Kevin Hoffer-Hawlik, Geoffrey P. Luke

ENGS 88 Honors Thesis (AB Students)

Photoacoustic (PA) imaging uses incident light to generate ultrasound signals within tissues. Using PA imaging to accurately measure hemoglobin concentration and calculate oxygenation (sO₂) requires prior tissue knowledge and costly computational methods. However, this thesis shows that machine learning algorithms can accurately and quickly estimate sO₂. absO₂luteU-Net, a convolutional neural network, was trained on Monte Carlo simulated multispectral PA data and predicted sO₂ with higher accuracy compared to simple linear unmixing, suggesting machine learning can solve the fluence estimation problem. This project was funded by the Kaminsky Family Fund and the Neukom Institute.

Applications Of Machine Learning In Nuclear Imaging And Radiation Detection, Shaikat Mahmood Galib

Doctoral Dissertations

"The main focus of this work is to use machine learning and data mining techniques to address some challenging problems that arise from nuclear data. Specifically, two problem areas are discussed: nuclear imaging and radiation detection. The techniques to approach these problems are primarily based on a variant of Artificial Neural Network (ANN) called Convolutional Neural Network (CNN), which is one of the most popular forms of 'deep learning' technique.

The first problem is about interpreting and analyzing 3D medical radiation images automatically. A method is developed to identify and quantify deformable image registration (DIR) errors from lung CT scans …

Calibrated Short Tr Recovery Mri For Rapid Measurement Of Brain-Blood Partition Coefficient And Correction Of Quantitative Cerebral Blood Flow, Scott William Thalman

Theses and Dissertations--Biomedical Engineering

The high prevalence and mortality of cerebrovascular disease has led to the development of several methods to measure cerebral blood flow (CBF) in vivo. One of these, arterial spin labeling (ASL), is a quantitative magnetic resonance imaging (MRI) technique with the advantage that it is completely non-invasive. The quantification of CBF using ASL requires correction for a tissue specific parameter called the brain-blood partition coefficient (BBPC). Despite regional and inter-subject variability in BBPC, the current recommended implementation of ASL uses a constant assumed value of 0.9 mL/g for all regions of the brain, all subjects, and even all species.

The …

Noninvasive Multimodal Diffuse Optical Imaging Of Vulnerable Tissue Hemodynamics, Mingjun Zhao

Theses and Dissertations--Biomedical Engineering

Measurement of tissue hemodynamics provides vital information for the assessment of tissue viability. This thesis reports three noninvasive near-infrared diffuse optical systems for spectroscopic measurements and tomographic imaging of tissue hemodynamics in vulnerable tissues with the goal of disease diagnosis and treatment monitoring. A hybrid near-infrared spectroscopy/diffuse correlation spectroscopy (NIRS/DCS) instrument with a contact fiber-optic probe was developed and utilized for simultaneous and continuous monitoring of blood flow (BF), blood oxygenation, and oxidative metabolism in exercising gastrocnemius. Results measured by the hybrid NIRS/DCS instrument in 37 subjects (mean age: 67 ± 6) indicated that vitamin D supplement plus aerobic training …

Quantification Of Myocardial Mechanics In Left Ventricles Under Inotropic Stimulation And In Healthy Right Ventricles Using 3d Dense Cmr, Zhan-Qiu Liu

Theses and Dissertations--Mechanical and Aerospace Engineering

Statistical data from clinical studies indicate that the death rate caused by heart disease has decreased due to an increased use of evidence-based medical therapies. This includes the use of magnetic resonance imaging (MRI), which is one of the most common non-invasive approaches in evidence-based health care research. In the current work, I present 3D Lagrangian strains and torsion in the left ventricle of healthy and isoproterenol-stimulated rats, which were investigated using Displacement ENcoding with Stimulated Echoes (DENSE) cardiac magnetic resonance (CMR) imaging. With the implementation of the 12-segment model, a detailed profile of regional cardiac mechanics was reconstructed for …

Effect Of Hypoxia On Spontaneous Neural Activity In The Cortex Of Neonate Mouse Pups, Krithikka Ravi Ms

Dissertations and Theses

Hypoxia caused by inadequate oxygenation has profound effects on the normal functioning of the brain in mammals. Acute or chronic hypoxic insults occur in the brain depending on the duration of hypoxic exposure. Hypoxia is known to occur in the human womb and exerts adverse effects on the developing fetus. Most of the ongoing research on hypoxia is performed on rodent brain slice taken from various brain regions using intracellular recording. Extensive work has been carried out to understand the effects of chronic hypoxia on the developing nervous system, specifically during intrauterine development. However, effects of acute hypoxia occurring perinatally, …

End-To-End Learning Via A Convolutional Neural Network For Cancer Cell Line Classification, Darlington A. Akogo, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Purpose: Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach: The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and …

Glioma Grading Using Structural Magnetic Resonance Imaging And Molecular Data, Syed M.S. Reza, Manar D. Samad, Zeina A. Shboul, Karra A. Jones, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

A glioma grading method using conventional structural magnetic resonance image (MRI) and molecular data from patients is proposed. The noninvasive grading of glioma tumors is obtained using multiple radiomic texture features including dynamic texture analysis, multifractal detrended fluctuation analysis, and multiresolution fractal Brownian motion in structural MRI. The proposed method is evaluated using two multicenter MRI datasets: (1) the brain tumor segmentation (BRATS-2017) challenge for high-grade versus low-grade (LG) and (2) the cancer imaging archive (TCIA) repository for glioblastoma (GBM) versus LG glioma grading. The grading performance using MRI is compared with that of digital pathology (DP) images in the …

Utilizing Immunopet To Measure Tumor Response To Treatment In Breast Cancer, Brooke Mcknight

Wayne State University Dissertations

With a broad spectrum of therapies available for treating breast cancer, the need for personalized medicine tailoring the cure according to phenotype is evident. Such an approach may be fully realized with the development of quantitative imaging technologies for disease detection, staging and diagnosis, without increasing patient burden. Immuno-positron emission tomography (PET) combines the targeted specificity of antibodies with the sensitivity of PET for whole body imaging by targeting molecular features amplified in lesions. ImmunoPET probes targeting different antigens and their utility to measure response to treatment were explored. 89Zr-trastuzumab was employed as a surrogate readout of Src inhibition after …

Textured Contact Lens Based Iris Presentation Attack In Uncontrolled Environment, Daksha Yadav

Graduate Theses, Dissertations, and Problem Reports (ETD)

The widespread use of smartphones has spurred the research in mobile iris devices. Due to their convenience, these mobile devices are also utilized in unconstrained outdoor conditions. At the same time, iris recognition in the visible spectrum has developed into an active area of research. These scenarios have necessitated the development of reliable iris recognition algorithms for such an uncontrolled environment. Additionally, iris presentation attacks such as textured contact lens pose a major challenge to current iris recognition systems.

Motivated by these factors, in this thesis, a detailed analysis of the effect of textured contact lenses on iris recognition in …

Optical Vortex And Poincaré Analysis For Biophysical Dynamics, Anindya Majumdar

Dissertations, Master's Theses and Master's Reports

Coherent light - such as that from a laser - on interaction with biological tissues, undergoes scattering. This scattered light undergoes interference and the resultant field has randomly added phases and amplitudes. This random interference pattern is known as speckles, and has been the subject of multiple applications, including imaging techniques. These speckle fields inherently contain optical vortices, or phase singularities. These are locations where the intensity (or amplitude) of the interference pattern is zero, and the phase is undefined.

In the research presented in this dissertation, dynamic speckle patterns were obtained through computer simulations as well as laboratory setups …