{"id":{"repo_id":"carleton","oai_identifier":"oai:carleton.scholaris.ca:20.500.14718/41295"},"canonical_url":"https://search.dev.ndltd.org/etd/carleton/oai:carleton.scholaris.ca:20.500.14718/41295","repository":{"repo_id":"carleton","name":"Carleton University","base_url":"https://carleton.scholaris.ca/server/oai/request"},"display":{"title":"Electrical Impedance Spectroscopy with Multi-modal Tissue Discrimination for Ultrasound-Guided Targeted Biopsy","abstract":"Prostate cancer diagnosis has undergone considerable evolution in recent years. Men with significant lesions observed via magnetic resonance imaging (MRI) typically undergo targeted biopsy. In a prostate biopsy procedure, ultrasound (US) is used to place a biopsy needle in lesion(s) identified via MRI for sampling. The lesion is not always visible in US, so proper needle placement is not guaranteed. Thus, false-negative results occur often, causing uncertainty in treatment. This thesis proposes an instrumented needle probe that uses electrical impedance spectroscopy to identify tissue at the needle tip in real-time, validated on an ex-vivo tissue dataset. Two data augmentation methods are proposed for improving classifiers trained on small datasets. Lastly, the thesis shows the ultrasonic vibrational potential can be measured with the probe and may provide information for tissue characterisation. The use of the probe for tissue identification could improve confidence in biopsy results and reduce procedure time.","abstract_html":"Prostate cancer diagnosis has undergone considerable evolution in recent years. Men with significant lesions observed via magnetic resonance imaging (MRI) typically undergo targeted biopsy. In a prostate biopsy procedure, ultrasound (US) is used to place a biopsy needle in lesion(s) identified via MRI for sampling. The lesion is not always visible in US, so proper needle placement is not guaranteed. Thus, false-negative results occur often, causing uncertainty in treatment. This thesis proposes an instrumented needle probe that uses electrical impedance spectroscopy to identify tissue at the needle tip in real-time, validated on an ex-vivo tissue dataset. Two data augmentation methods are proposed for improving classifiers trained on small datasets. Lastly, the thesis shows the ultrasonic vibrational potential can be measured with the probe and may provide information for tissue characterisation. 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