{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/33960"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/33960","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Critical Issues in the Processing of cDNA Microarray Images","abstract":"Microarray technology enables simultaneous gene expression level monitoring for thousands of genes. While this technology has now been recognized as a powerful and cost-effective tool for large-scale analysis, the many systematic sources of experimental variations introduce inherent errors in the extracted data. Data is gathered by processing scanned images of microarray slides. Therefore robust image processing is particularly important and has a large impact on downstream analysis. The processing of the scanned images can be subdivided in three phases: gridding, segmentation and data extraction. To measure the gene expression levels, the processing of cDNA microarray images must overcome a large set of issues in these three phases that motivates this study. This study presents automatic gridding methods and compares their performances. Two segmentation techniques already used, the Seeded Region Growing Algorithm and the Mann-Whitney Test, are examined. We present limitations of these techniques. Finally, we studied the data extraction method used in MicroArray Suite (MS), a microarray analysis software, via synthetic images and explain its intricacies.","abstract_html":"Microarray technology enables simultaneous gene expression level monitoring for thousands of genes. While this technology has now been recognized as a powerful and cost-effective tool for large-scale analysis, the many systematic sources of experimental variations introduce inherent errors in the extracted data. Data is gathered by processing scanned images of microarray slides. Therefore robust image processing is particularly important and has a large impact on downstream analysis. The processing of the scanned images can be subdivided in three phases: gridding, segmentation and data extraction. To measure the gene expression levels, the processing of cDNA microarray images must overcome a large set of issues in these three phases that motivates this study. This study presents automatic gridding methods and compares their performances. Two segmentation techniques already used, the Seeded Region Growing Algorithm and the Mann-Whitney Test, are examined. We present limitations of these techniques. Finally, we studied the data extraction method used in MicroArray Suite (MS), a microarray analysis software, via synthetic images and explain its intricacies.","abstract_has_math":false,"creators":["Jouenne, Vincent Y."],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Computer Science","degree_department":"Computer Science","school":null,"contributors":[],"advisors":[],"committee_chairs":["Heath, Lenwood S."],"committee_members":["Struble, Craig A.","Alscher, Ruth G."],"year":2001,"date_issued":"2001-06-28","date_published":"2001-06-28","updated_at":"2026-07-22T22:19:48Z","subjects":["Mann-Whitney Test","Image Processing","Segmentation","Gene Expression","Data Extraction","Seeded Region Growing Algorithm","Automatic Gridding"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-07112001-112357"],"render_values":[{"text":"etd-07112001-112357","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/33960","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Heath, Lenwood S."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Struble, Craig A.","Alscher, Ruth G."]},{"key":"dc:contributor.department","label":"Department","values":["Computer Science"]},{"key":"dc:creator","label":"Author","values":["Jouenne, Vincent Y."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T20:41:17Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T20:41:17Z","2002-07-13"]},{"key":"dc:date.issued","label":"Date","values":["2001-06-28"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mann-Whitney Test","Image Processing","Segmentation","Gene Expression","Data Extraction","Seeded Region Growing Algorithm","Automatic Gridding"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-07112001-112357"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/33960"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Microarray technology enables simultaneous gene expression level monitoring for thousands of genes. While this technology has now been recognized as a powerful and cost-effective tool for large-scale analysis, the many systematic sources of experimental variations introduce inherent errors in the extracted data. Data is gathered by processing scanned images of microarray slides. Therefore robust image processing is particularly important and has a large impact on downstream analysis. The processing of the scanned images can be subdivided in three phases: gridding, segmentation and data extraction. To measure the gene expression levels, the processing of cDNA microarray images must overcome a large set of issues in these three phases that motivates this study. This study presents automatic gridding methods and compares their performances. Two segmentation techniques already used, the Seeded Region Growing Algorithm and the Mann-Whitney Test, are examined. We present limitations of these techniques. Finally, we studied the data extraction method used in MicroArray Suite (MS), a microarray analysis software, via synthetic images and explain its intricacies."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:title","label":"Title","values":["Critical Issues in the Processing of cDNA Microarray Images"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Heath, Lenwood S."],"dc:contributor.committeemember":["Struble, Craig A.","Alscher, Ruth G."],"dc:contributor.department":["Computer Science"],"dc:creator":["Jouenne, Vincent Y."],"dc:date.accessioned":["2014-03-14T20:41:17Z"],"dc:date.available":["2014-03-14T20:41:17Z","2002-07-13"],"dc:date.issued":["2001-06-28"],"dc:description.abstract":["Microarray technology enables simultaneous gene expression level monitoring for thousands of genes. While this technology has now been recognized as a powerful and cost-effective tool for large-scale analysis, the many systematic sources of experimental variations introduce inherent errors in the extracted data. Data is gathered by processing scanned images of microarray slides. Therefore robust image processing is particularly important and has a large impact on downstream analysis. The processing of the scanned images can be subdivided in three phases: gridding, segmentation and data extraction. To measure the gene expression levels, the processing of cDNA microarray images must overcome a large set of issues in these three phases that motivates this study. This study presents automatic gridding methods and compares their performances. Two segmentation techniques already used, the Seeded Region Growing Algorithm and the Mann-Whitney Test, are examined. We present limitations of these techniques. Finally, we studied the data extraction method used in MicroArray Suite (MS), a microarray analysis software, via synthetic images and explain its intricacies."],"dc:description.degree":["Master of Science"],"dc:identifier.other":["etd-07112001-112357"],"dc:identifier.uri":["http://hdl.handle.net/10919/33960"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Mann-Whitney Test","Image Processing","Segmentation","Gene Expression","Data Extraction","Seeded Region Growing Algorithm","Automatic Gridding"],"dc:title":["Critical Issues in the Processing of cDNA Microarray Images"],"dc:type":["Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:48Z"}