Engineering Commons^™

Hybrid Power Spectral And Wavelet Image Roughness Analysis, Basel White

Electronic Theses and Dissertations

The Two-Dimensional Wavelet Transform Modulus Maxima (2D WTMM) sliding window methodology has proven to be a robust approach, in particular for the extraction of the Hurst (H) roughness exponent from grayscale mammograms. The power spectrum is a computational analysis based on the Fourier transform that can be used to estimate the roughness of a scale-invariant image or region via the calculation of H. We aim to examine how the calculation of H in fractional Brownian motion (fBm) images and mammograms can be improved. fBm images are generated for H ∈ [0.00,1.00] for testing through the previous 2D …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Development Of Quantitative Molecular Photoacoustic Imaging For Noninvasive Cancer Diagnostics, Cayla Zandbergen

Dissertations & Theses (Open Access)

Traditional diagnostic imaging provides clinicians with anatomical information that guides both diagnosis and treatment planning; however, once a tumor has progressed enough to be visible, it has often reached an advanced stage. Molecular imaging techniques allow for real-time visualization of chemical and biological processes via imaging of specific biomarkers, which can facilitate detection of malignancies before they become visible. One biomarker of interest is blood oxygen saturation (SO₂) due to its correlation with hypoxia, which is associated with increased tumor malignancy; some studies have also established SO₂ as an independent biomarker of disease progression. Additionally, because cancerous …

The Impact Of Nanopulse Treatment On The Tumor Microenvironment In Breast Cancer: Overturning The Treg Immunosuppressive Dominance, Anthony Nanajian

Biomedical Sciences Theses & Dissertations

Nanopulse treatment (NPT) is a high-power electric engineering modality that has been shown to be an effective local tumor treatment approach in multiple cancer models. Our previous studies on the orthotopic 4T1-luc breast cancer model demonstrated that NPT ablated local tumors. The treatment consequently conferred protection against a second live tumor challenge and minimized spontaneous metastasis. This study aims to understand how NPT mounts a potent immune response in a predominantly immunosuppressive tumor.

NPT changed the local and systemic dynamics of immunosuppressive cells by significantly reducing the numbers of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages …

Markov Decision Process Approach To Strategize National Breast Cancer Screening Policy In Data-Limited Settings, Vijeta Deshpande

Masters Theses

Early diagnosis is a promising strategy to reduce premature mortalities and for optimal use of resources. But the absence of mathematical models specific to the data settings in LMIC’s impedes the construction of economic analysis necessary for decision-makers in the development of cancer control programs. This thesis presents a new methodology for parameterizing the natural history model of breast cancer based on data availabilities in low and middle income countries, and formulation of a control optimization problem to find the optimal screening schedule for mammography screening, solved using dynamic programming. As harms and benefits are known to increase with the …

Characterization Of Murine Breast Cancer Cell Lines For Anti-Cancer Vaccine, Haven N. Frazier

Biological Sciences Undergraduate Honors Theses

Breast cancer is the most commonly diagnosed cancer in women and the second leading cause of cancer death among women in the United States (1). While treatments involving radiation and chemotherapy currently exist, disease must be detected early in order for the treatments to be somewhat effective, and there is no effective treatment after metastasis occurs (2). Additionally, current therapies do not mitigate tumor immunosuppression. Decreasing the tumor-associated immunosuppressive conditions while activating antitumor immunity could prevent recurrence and metastasis, possibly leading to an effective treatment for cancer (3). Tumor cell vaccines could possibly address this issue and have become a …

Numerical Simulation Of Terahertz Wave Interaction With Breast Cancer Tumor Tissue Sections, Abayomi Omotola Omolewu

Graduate Theses and Dissertations

This thesis presents numerical simulation of terahertz (THz) wave interaction with breast cancer tumor tissue sections. The obtained results are expressed in THz images of heterogeneous material that mimics the excised breast cancer tissue sections. The finite-element software package ANSYS High Frequency Structural Simulator (HFSS) was used in this work. HFSS is a full wave frequency domain three-dimensional (3D) electromagnetic simulation package. In this work, four breast cancer tissue models based on pathology images were simulated and images of the models were obtained at 1 THz. An incident Gaussian beam was raster scanned over tissue model configurations and the reflected …

The Application Of Innovative High-Throughput Techniques To Serum Biomarker Discovery, Izabela Debkiewicz Karbassi

Theses and Dissertations in Biomedical Sciences

Time-of-flight mass spectrometry continues to evolve as a promising technique for serum protein expression profiling and biomarker discovery. As seen in our initial SELDI-TOF MS and MALDI-TOF MS profiling study of serum for the assessment of breast cancer risk, many profiling strategies typically employ single chemical affinity beads or surfaces to decrease sample complexity of dynamic fluids like serum. However, most proteins, captured on a particular surface or bead, are not resolved in the lower mass range where mass spectrometers are most effective. To this end we have designed an expression profiling workflow that utilizes immobilized trypsin paramagnetic beads in …

Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94

Doctoral Dissertations

The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.

Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …