Classifying Breast Tumors using Medical Microwave Radar Imaging

Medical Microwave Imaging (MMI) has been studied in the past years to develop techniques to detect breast cancer at the earliest stages of development. Particularly, ultra-wideband (UWB) micro-wave radar imaging systems can detect and classify tumors as benign or malignant since this technique yields information about the size and shape of tumors. In this study we used this technology to classify tumors. The primary goal of this dissertation is two-folded. First, producing breast tumor numerical mod-els and using them in 2D MMI simulations that recreate the conditions of a UWB microwave radar imaging system. The breast tumor numerical produced resemble real tumor morphologies since they are made from breast MRI exams segmentations. Second, the data of the backscattered UWB microwave signals produced by the MMI simulations was used to classify tumors according to their size and histol-ogy, which is relevant to assess potential of UWB microwave radar imaging systems as a reliable alter-native method for the classification of breast tumors in the field of Medical Microwave Imaging. The Classification Algorithms used in this work were Pseudo Linear Discriminant Analysis (Pseudo-LDA), Pseudo Quadratic Discriminant Analysis (pseudo-QDA), and k-Nearest Neighbors (KNN), alongside with a feature extraction algorithm – Principal Component Analysis (PCA).A Imagem Médica por Microondas (do inglês, MMI) tem sido estudada nos últimos anos de forma a desenvolver técnicas de deteção do cancro da mama nas primeiras fases de desenvolvimento. Em particular, os sistemas de imagem de radar por microondas em banda ultralarga (do inglês UWB) podem detetar e classificar os tumores como benignos ou malignos, uma vez que esta técnica produz informação sobre o tamanho e a forma dos tumores. Neste estudo, utilizámos esta tecnologia para classificar os tumores. A dissertação tem dois objetivos principais. Primeiro, produzir fantomas de tumores mamários e utilizá-los em simulações de MMI em 2D que recriam as condições de um sistema de imagem de radar por microondas UWB. Os fantomas numéricos de tumores mamários produzidos possuem morfologias semelhantes a tumores reais, uma vez que são feitos a partir de segmentações de exames de ressonância magnética da mama. Em segundo lugar, as reflexões dos sinais de microondas UWB produzidos pelas simulações de MMI foram utilizados para classificar tumores de acordo com o seu tamanho e histologia, o que é relevante para avaliar o potencial dos sistemas de imagem de radar por microondas UWB como um método alternativo e fiável para a classificação de tumores mamários no campo da MMI. Os Algo-ritmos de Classificação utilizados neste trabalho foram a Pseudo Linear Discriminant Analysis (Pseudo-LDA), Pseudo Quadratic Discriminant Analysis (pseudo-QDA), e a K-Nearest Neighbors (KNN), jun-tamente com um algoritmo de extração de features - Análise de Componentes Principais (do inglês PCA)

Webcam-based distance and surface estimation system for microwave imaging

One of the critical steps in Medical Microwave Imaging (MMWI) algorithms is the calculation of the distances between the antenna and the synthetical focal point, due to the different propagation velocities in the tissues and background medium. In fact, it has a major influence on the image accuracy. As a result, it is very important to have a priori information about the shape of the body part under examination. Here we propose a low cost optical system based on a single commercial webcam. We validate the new system by showing an application to breast imaging, where we reconstruct the scatterers inside the breast using the real and estimated shapes. The results show very good resemblance, thus proving the new system supplies a reliable estimation of the breast shape.info:eu-repo/semantics/publishedVersio

Experimental Analysis on Effectiveness of Confocal Algorithm for Radar Based Breast Cancer Detection

Breast cancer is one of the most commonly diagnosed cancers in females in UK [1]. Early breast cancer detection which has recently been gaining a lot of consideration within the research community and the most important for a quick and effective treatment of the cancer is early detection. UWB radar based microwave imaging for early breast cancer detection is one of the most promising and attractive screening techniques currently under research. This technique offers several advantages such as low cost, better patient comfort, non-ionising and non-invasive radiation compared to X-Ray mammography. In this technique the breast is illuminated from various points with short UWB microwave pulse(s) and the collected backscattered energy is then processed to identify the presence and location of the tumour. In this thesis experimental measurement of the reflection coefficient in complex frequency domain is obtained from Vector Network Analyzer (VNA E5071) when the antenna is exposed to the environment and when the antenna is exposed to breast phantom. The tumor is simulated with different materials to investigate the effectiveness of the Confocal Microwave Imaging Algorithm for breast cancer detection. In addition, we used the materials at different depths to determine the effect of antenna distance to that of the tumor response. The Confocal Microwave Imaging (CMI) Algorithm for breast cancer detection is an easy and robust technique for tumor detection, which is used to approximate the precise location of the tumor. CMI is based on illuminating the breast with the UWB pulse from different antenna locations. The relative arrival times & amplitudes of the backscatter signals is used to estimate the location of the tumor. We applied the Confocal Algorithm in this study to the numerical data generated with the VNA and analyzed the results with different material(s) as tumor at different depth to verify its ability to estimate a tumor response

Tissue Mimicking Materials for Multi-Modality Breast Phantoms

The paper proposes two different Tissue Mimicking Material (TMM) techniques for the development of breast phantoms which are suitable for multi-modality imaging. In particular, the focus is on the behavior of dielectric and acoustic properties when fat, sodium chloride and sugar are added to the mixtures

Microwave breast imaging using a dry setup

This article demonstrates for the first time, both numerically and experimentally, the feasibility of radar-based microwave imaging of anthropomorphic heterogeneously dense breasts in prone position, requiring no immersion liquid. The dry, contactless approach greatly simplifies the setup, favors patient comfort, and further avoids lengthy sanitation procedures after each exam. We use a radar-type technique with the antennas distributed in cylindrical configuration around the breast phantom. The reflectivity map is reconstructed using a wave-migration algorithm in the frequency domain. This article presents new developed strategies to cope with the challenges of a dry setup, namely increased skin artifact due to the concomitant absence of matching liquid and nonuniform breast shape. We propose an iterative and adaptive algorithm based on singular value decomposition that effectively removes the skin backscattering under the abovementioned conditions. It is compatible with automatic processing, and computationally fast. One of its inputs is the breast three-dimensional surface information, and its distance to the antennas, all obtained automatically from a proposed low-cost procedure based on a webcam. The imaging method is reasonably resilient to the presence of fibroglandular tissues, and to uncertainties of tissue permittivity. Another tackled challenge is the miniaturization of the antenna in air, which is achieved with an optimized balanced antipodal Vivaldi of the same size as counterparts used in dense immersion liquids. Finally, all the building blocks are combined to demonstrate experimentally the overall dry system performance, with very good detection of the tumor at three different positions in the breast, even in low-contrast scenarios.info:eu-repo/semantics/acceptedVersio

Microwave power imaging for ultra-wide band early breast cancer detection

Due to the critical need for complementary or/and alternative modalities to current X-ray mammography for early-stage breast cancer detection, a 3D active microwave imaging system has been developed. This thesis presents a detailed method for rapid, high contrast microwave imaging for the purpose of breast survey. In the proposed imaging system, several transmitters polarized in different directions take turns sending out a low-power UWB pulse into the breast; backscattered signals are recorded by a synthetic aperture antenna array. These backscattered signals are passed through a beamformer, which spatially focuses the waveforms to image backscattered energy as a function of location in the breast. A simple Delay-and-Sum algorithm is applied to test the proposed multistatic multi-polarized detection scheme. The obtained 2-D and 3-D numerical results have demonstrated the feasibility and superiority of detecting small malignant breast tumors using our antenna strategy. An improved algorithm of microwave power imaging for detecting small breast tumors within an MRI-derived phantom is also introduced. Our imaging results demonstrate that a high-quality image can be reached without solving the inverse problem. To set up an experimental system for future clinical investigation, we developed two Vivaldi antennas, which have a notable broad band property, good radiation pattern, and a suitable size for breast cancer detection. Finally, an antenna array which consists of eight proposed Vivaldi antennas is introduced. By conveniently moving up/down and rotating this antenna array, it can be used for the multistatic breast cancer imaging and qualified for our multi-polarized scan mode