ARAN - Access to Research at NUI Galway

Ultrawideband Radar for the Early Detection of Cancer Within the Heterogeneous Breast

ARAN - Access to Research at NUI Galway

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dc.contributor.advisor Jones, Edward
dc.contributor.advisor Glavin, Martin
dc.contributor.author Byrne, Dallan
dc.date.accessioned 2012-11-07T12:50:25Z
dc.date.available 2012-11-07T12:50:25Z
dc.date.issued 2012-01-18
dc.identifier.uri http://hdl.handle.net/10379/3035
dc.description.abstract Ultrawideband (UWB) microwave imaging is an emerging breast screening modality based on the electromagnetic reflections generated by the dielectric contrast between soft tissue types within the breast at microwave frequencies, most notably between malignant and fatty tissue. However, the breast can contain significant amounts of fibroglandular or fibroconnective tissues, which reduce the dielectric contrast between healthy and cancerous tissue and limits the effectiveness of UWB imaging algorithms. This dissertation focuses on UWB scanning techniques to detect cancer, with a par- ticular focus on the dielectrically heterogeneous breast. The work can be viewed in two parts: UWB breast cancer imaging and UWB breast cancer detection. The first part focuses on UWB beamforming algorithms and their ability to image a tumour response when the breast contains significant levels of glandular tissue. A number of Data Independent beamforming methods are compared using metrics, where signal data are generated from 3D Finite-Difference Time-Domain (FDTD) models adapted from MRI-derived phantoms. A novel extension of a Data Adap- tive imaging algorithm is presented and is shown to significantly outperform existing beamformers, particularly in a dielectrically heterogeneous breast. The application of contrast agents with UWB imaging methods is shown to successfully image non- palpable tumours when significant levels of fibroglandular tissue are present. The second area of study focuses on using a Support Vector Machine (SVM) based UWB cancer detection system to identify tumour backscatter within the received UWB signal data. The algorithm is extended to process the temporal changes between signals using an SVM and is shown to successfully detect non-palpable tumours when fluctuations in glandular tissue density and cancerous growth can occur during the time between scans. en_US
dc.subject Ultrawideband en_US
dc.subject Breast imaging en_US
dc.subject Beamforming en_US
dc.subject Electrical and Electronic Engineering en_US
dc.subject Engineering and Informatics en_US
dc.title Ultrawideband Radar for the Early Detection of Cancer Within the Heterogeneous Breast en_US
dc.type Thesis en_US
dc.contributor.funder Ircset Enterprise Partnership Scheme en_US
dc.contributor.funder Hewlett Packard en_US
dc.local.note Ultrawideband (UWB) microwave imaging is an emerging breast screening modality based on the electromagnetic reflections generated by the dielectric contrast between soft tissue types within the breast at microwave frequencies, most notably between malignant and fatty tissue. However, the breast can contain significant amounts of fibroglandular or fibroconnective tissues, which reduce the dielectric contrast between healthy and cancerous tissue and limits the effectiveness of UWB imaging algorithms. This dissertation focuses on UWB scanning techniques to detect cancer, with a par- ticular focus on the dielectrically heterogeneous breast. The work can be viewed in two parts: UWB breast cancer imaging and UWB breast cancer detection. The first part focuses on UWB beamforming algorithms and their ability to im- age a tumour response when the breast contains significant levels of glandular tissue. A number of Data Independent beamforming methods are compared using metrics, where signal data are generated from 3D Finite-Difference Time-Domain (FDTD) models adapted from MRI-derived phantoms. A novel extension of a Data Adap- tive imaging algorithm is presented and is shown to significantly outperform existing beamformers, particularly in a dielectrically heterogeneous breast. The application of contrast agents with UWB imaging methods is shown to successfully image non- palpable tumours when significant levels of fibroglandular tissue are present. The second area of study focuses on using a Support Vector Machine (SVM) based UWB cancer detection system to identify tumour backscatter within the received UWB signal data. The algorithm is extended to process the temporal changes between signals using an SVM and is shown to successfully detect non-palpable tumours when fluctuations in glandular tissue density and cancerous growth can occur during the time between scans. en_US
dc.local.final Yes en_US

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