{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/23100"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/23100","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Boundary detection in ultrasonic speckle","abstract":"\"This dissertation considers the problem of detecting boundaries in ultrasound speckle imagery. For physiological reasons, we argue that boundaries between tissue layers appear as lines in ultrasound scans and approach the boundary detection problem as one of detecting lines of unknown orientation. We define a set of \"\"sticks,\"\" short line segments of variable orientation that can locally approximate the boundaries. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for sticks of unknown orientation in fully developed speckle and compare the optimal detector to several suboptimal detection rules which are more computationally efficient. We show that when the underlying Gaussian random process underlying speckle noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. The basic technique is then extended in a number of ways to improve its performance. We investigate the effect of varying the size and shape of the sticks and show that these variations affect the performance of the algorithm in very fundamental ways, for example, by making it more or less sensitive to thinner or more tightly curving boundaries. We also present a means of improving performance by estimating the distribution function of the orientation of the line passing through each point. Next, we show that images can be \"\"stained\"\" for easier visual interpretation by applying to each pixel a false color whose hue is related to the orientation of the most prominent line segment at that point. Finally, an analysis is given of boundary detection approaches in radio-frequency ultrasound.\"","abstract_html":""This dissertation considers the problem of detecting boundaries in ultrasound speckle imagery. For physiological reasons, we argue that boundaries between tissue layers appear as lines in ultrasound scans and approach the boundary detection problem as one of detecting lines of unknown orientation. We define a set of ""sticks,"" short line segments of variable orientation that can locally approximate the boundaries. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for sticks of unknown orientation in fully developed speckle and compare the optimal detector to several suboptimal detection rules which are more computationally efficient. We show that when the underlying Gaussian random process underlying speckle noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. The basic technique is then extended in a number of ways to improve its performance. We investigate the effect of varying the size and shape of the sticks and show that these variations affect the performance of the algorithm in very fundamental ways, for example, by making it more or less sensitive to thinner or more tightly curving boundaries. We also present a means of improving performance by estimating the distribution function of the orientation of the line passing through each point. Next, we show that images can be ""stained"" for easier visual interpretation by applying to each pixel a false color whose hue is related to the orientation of the most prominent line segment at that point. Finally, an analysis is given of boundary detection approaches in radio-frequency ultrasound."","abstract_has_math":false,"creators":["Czerwinski, Richard Norman"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":["Jones, Douglas L.","O'Brien, William D."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T14:02:11Z","date_published":"2011-05-07T14:02:11Z","updated_at":"2026-07-22T22:25:21Z","subjects":["Engineering, Electronics and Electrical"],"languages":["eng"],"rights":["Copyright 1996 Czerwinski, Richard Norman"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9780591197853","AAI9712244","(UMI)AAI9712244"],"render_values":[{"text":"9780591197853","href":null,"code":true},{"text":"AAI9712244","href":null,"code":true},{"text":"(UMI)AAI9712244","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/23100","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jones, Douglas L.","O'Brien, William D."]},{"key":"dc:creator","label":"Author","values":["Czerwinski, Richard Norman"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T14:02:11Z","10000-01-01","1996"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Electronics and Electrical"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1996 Czerwinski, Richard Norman"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9780591197853","AAI9712244","(UMI)AAI9712244","http://hdl.handle.net/2142/23100"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["\"This dissertation considers the problem of detecting boundaries in ultrasound speckle imagery. For physiological reasons, we argue that boundaries between tissue layers appear as lines in ultrasound scans and approach the boundary detection problem as one of detecting lines of unknown orientation. We define a set of \"\"sticks,\"\" short line segments of variable orientation that can locally approximate the boundaries. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for sticks of unknown orientation in fully developed speckle and compare the optimal detector to several suboptimal detection rules which are more computationally efficient. We show that when the underlying Gaussian random process underlying speckle noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. The basic technique is then extended in a number of ways to improve its performance. We investigate the effect of varying the size and shape of the sticks and show that these variations affect the performance of the algorithm in very fundamental ways, for example, by making it more or less sensitive to thinner or more tightly curving boundaries. We also present a means of improving performance by estimating the distribution function of the orientation of the line passing through each point. Next, we show that images can be \"\"stained\"\" for easier visual interpretation by applying to each pixel a false color whose hue is related to the orientation of the most prominent line segment at that point. Finally, an analysis is given of boundary detection approaches in radio-frequency ultrasound.\"","Made available in DSpace on 2011-05-07T14:02:11Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9712244.pdf: 4200073 bytes, checksum: 0a30ae2efc7ec3cfd1ae837a1661abc6 (MD5) Previous issue date: 1996","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T15:02:10Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:29:33-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["Boundary detection in ultrasonic speckle"]}]}],"canonical_facts":{"dc:contributor":["Jones, Douglas L.","O'Brien, William D."],"dc:creator":["Czerwinski, Richard Norman"],"dc:date":["2011-05-07T14:02:11Z","10000-01-01","1996"],"dc:description":["\"This dissertation considers the problem of detecting boundaries in ultrasound speckle imagery. For physiological reasons, we argue that boundaries between tissue layers appear as lines in ultrasound scans and approach the boundary detection problem as one of detecting lines of unknown orientation. We define a set of \"\"sticks,\"\" short line segments of variable orientation that can locally approximate the boundaries. Using the physical principles that account for the speckle phenomenon, we derive the optimal detector for sticks of unknown orientation in fully developed speckle and compare the optimal detector to several suboptimal detection rules which are more computationally efficient. We show that when the underlying Gaussian random process underlying speckle noise is uncorrelated, a very simple suboptimal detection rule is nearly optimal, and that even in colored speckle, a related class of detectors can approach optimal performance. The basic technique is then extended in a number of ways to improve its performance. We investigate the effect of varying the size and shape of the sticks and show that these variations affect the performance of the algorithm in very fundamental ways, for example, by making it more or less sensitive to thinner or more tightly curving boundaries. We also present a means of improving performance by estimating the distribution function of the orientation of the line passing through each point. Next, we show that images can be \"\"stained\"\" for easier visual interpretation by applying to each pixel a false color whose hue is related to the orientation of the most prominent line segment at that point. Finally, an analysis is given of boundary detection approaches in radio-frequency ultrasound.\"","Made available in DSpace on 2011-05-07T14:02:11Z (GMT). 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