Ultrasound tomography is an emerging modality for imaging breast tissue for the detection of disease. Using the principles of full waveform inversion, high-resolution quantitative sound speed and attenuation maps of the breast can be created. In this thesis, we introduce some basic principles of imaging breast disease and the formalism of sound wave propagation. We present numerical methods to model acoustic wave propagation as well methods to solve the corresponding inverse problem. Numerical simulations of sound speed and attenuation reconstructions are used to assess the efficacy of the algorithm. A careful review of the preprocessing techniques needed for the successful inversion of acoustic data is presented. Ex vivo and in vivo sound speed reconstructions highlight the significant improvements that are made upon commonly used travel time sound speed reconstruction methods. Note that we do not present ex vivo or in vivo attenuation reconstructions in this thesis. For the sound speed images, the higher resolution and contrast of the waveform method will hopefully allow a radiologist to make a more informed diagnosis of breast disease. A comparison of full waveform sound speed imaging to MRI shows a great deal of concordant findings. Lastly, we give examples of the use of full waveform inversion sound speed imaging in a clinical setting.
","abstract_html":"<p>Ultrasound tomography is an emerging modality for imaging breast tissue for the detection of disease. Using the principles of full waveform inversion, high-resolution quantitative sound speed and attenuation maps of the breast can be created. In this thesis, we introduce some basic principles of imaging breast disease and the formalism of sound wave propagation. We present numerical methods to model acoustic wave propagation as well methods to solve the corresponding inverse problem. Numerical simulations of sound speed and attenuation reconstructions are used to assess the efficacy of the algorithm. A careful review of the preprocessing techniques needed for the successful inversion of acoustic data is presented. Ex vivo and in vivo sound speed reconstructions highlight the significant improvements that are made upon commonly used travel time sound speed reconstruction methods. Note that we do not present ex vivo or in vivo attenuation reconstructions in this thesis. For the sound speed images, the higher resolution and contrast of the waveform method will hopefully allow a radiologist to make a more informed diagnosis of breast disease. A comparison of full waveform sound speed imaging to MRI shows a great deal of concordant findings. Lastly, we give examples of the use of full waveform inversion sound speed imaging in a clinical setting.</p>","abstract_has_math":false,"creators":["Sandhu, Gursharan Singh"],"institution":null,"degree_name":"Ph.D.","degree_level":"Open Access Dissertation","degree_discipline":"Physics and Astronomy","degree_department":null,"school":null,"contributors":["Zhi-Feng Huang","Neb Duric"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-01T08:00:00Z","date_published":"2015-01-01T08:00:00Z","updated_at":"2026-07-24T06:00:09Z","subjects":["Breast Cancer Detection","Clinical Breast Imaging","Inverse Problems","Ultrasound Waveform Tomography","Bioimaging and Biomedical Optics","Physics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wayne.edu/oa_dissertations/1295","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhi-Feng Huang","Neb Duric"]},{"key":"dc:creator","label":"Author","values":["Sandhu, Gursharan Singh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-10-22T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Physics and Astronomy"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Breast Cancer Detection","Clinical Breast Imaging","Inverse Problems","Ultrasound Waveform Tomography","Bioimaging and Biomedical Optics","Physics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wayne.edu/oa_dissertations/1295"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Ultrasound tomography is an emerging modality for imaging breast tissue for the detection of disease. Using the principles of full waveform inversion, high-resolution quantitative sound speed and attenuation maps of the breast can be created. In this thesis, we introduce some basic principles of imaging breast disease and the formalism of sound wave propagation. We present numerical methods to model acoustic wave propagation as well methods to solve the corresponding inverse problem. Numerical simulations of sound speed and attenuation reconstructions are used to assess the efficacy of the algorithm. A careful review of the preprocessing techniques needed for the successful inversion of acoustic data is presented. Ex vivo and in vivo sound speed reconstructions highlight the significant improvements that are made upon commonly used travel time sound speed reconstruction methods. Note that we do not present ex vivo or in vivo attenuation reconstructions in this thesis. For the sound speed images, the higher resolution and contrast of the waveform method will hopefully allow a radiologist to make a more informed diagnosis of breast disease. A comparison of full waveform sound speed imaging to MRI shows a great deal of concordant findings. Lastly, we give examples of the use of full waveform inversion sound speed imaging in a clinical setting.
"]},{"key":"dc:title","label":"Title","values":["Frequency Domain Ultrasound Waveform Tomography Breast Imaging"]}]}],"canonical_facts":{"dc:contributor":["Zhi-Feng Huang","Neb Duric"],"dc:creator":["Sandhu, Gursharan Singh"],"dc:date.available":["2016-10-22T07:00:00Z"],"dc:description.abstract":["Ultrasound tomography is an emerging modality for imaging breast tissue for the detection of disease. Using the principles of full waveform inversion, high-resolution quantitative sound speed and attenuation maps of the breast can be created. In this thesis, we introduce some basic principles of imaging breast disease and the formalism of sound wave propagation. We present numerical methods to model acoustic wave propagation as well methods to solve the corresponding inverse problem. Numerical simulations of sound speed and attenuation reconstructions are used to assess the efficacy of the algorithm. A careful review of the preprocessing techniques needed for the successful inversion of acoustic data is presented. Ex vivo and in vivo sound speed reconstructions highlight the significant improvements that are made upon commonly used travel time sound speed reconstruction methods. Note that we do not present ex vivo or in vivo attenuation reconstructions in this thesis. For the sound speed images, the higher resolution and contrast of the waveform method will hopefully allow a radiologist to make a more informed diagnosis of breast disease. A comparison of full waveform sound speed imaging to MRI shows a great deal of concordant findings. Lastly, we give examples of the use of full waveform inversion sound speed imaging in a clinical setting.
"],"dc:identifier":["https://digitalcommons.wayne.edu/oa_dissertations/1295"],"dc:subject":["Breast Cancer Detection","Clinical Breast Imaging","Inverse Problems","Ultrasound Waveform Tomography","Bioimaging and Biomedical Optics","Physics"],"dc:title":["Frequency Domain Ultrasound Waveform Tomography Breast Imaging"],"thesis:degree_discipline":["Physics and Astronomy"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T06:00:09Z"}