{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/79355"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/79355","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Algorithmic Approaches for Determining Spatial Patterns in Several Biomedical Applications","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Chen, Zihe"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Xu, Jinhui","Chemical and Biological Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-04-04T20:30:46Z","date_published":"2019-04-04T20:30:46Z","updated_at":"2026-07-27T19:05:16Z","subjects":["computer science"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/79355","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Xu, Jinhui","Chemical and Biological Engineering"]},{"key":"dc:creator","label":"Author","values":["Chen, Zihe"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-04-04T20:30:46Z","2019","2018-12-19 02:05:36"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["computer science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/79355"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Finding the structural pattern from a set of objects is a commonly encountered prototype learning problem and has a wide range of applications in machine learning and pattern recognition. In cell biology, there is growing need of finding the structural pattern of chromosomes with help of computer algorithms. Unlike general datasets, biological dataset of cell nucleus from a population of cells usually contains biological semantics that should be treated with special algorithms. Endovascular coiling (or simply, coiling) is a primary treatment for intra-cranial aneurysm, which deploys a thin and detachable metal wire inside the aneurysm so as to prevent its rupture. Emerging evidence from medical research and clinical practice has suggested that the coil con- figuration inside the aneurysm plays a vital role in properly treating aneurysm and predicting its outcome.In this thesis, we mainly focus on developing algorithms for the above two types of applications. For the first area, we proposed two algorithms : 1) mining k-median graphs from chromosome association graphs, where each median graph is a representative structure of chromosome associations of a subset of the cells in the population; 2) finding rigid sub-structure patterns of chromosome topology structures, which can be viewed as 3D point-sets. Different from most of the existing models for pattern reconstruction (where each input point-set is often treated as a single structure), our model views each input point-set as a collection of k rigid substructures, and aims to extract similar rigid substructures from each input point-set to form k rigid clusters.For the second area, we propose a novel virtual coiling technique, called Ball Wind- ing, for generating deployable coil configuration with ensured blocking ability (for the first time). It can be used as an automatic tool for virtually simulating coiling before its implantation and thus optimizes such treatments."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Algorithmic Approaches for Determining Spatial Patterns in Several Biomedical Applications"]}]}],"canonical_facts":{"dc:contributor":["Xu, Jinhui","Chemical and Biological Engineering"],"dc:creator":["Chen, Zihe"],"dc:date":["2019-04-04T20:30:46Z","2019","2018-12-19 02:05:36"],"dc:description":["Ph.D.","Finding the structural pattern from a set of objects is a commonly encountered prototype learning problem and has a wide range of applications in machine learning and pattern recognition. In cell biology, there is growing need of finding the structural pattern of chromosomes with help of computer algorithms. Unlike general datasets, biological dataset of cell nucleus from a population of cells usually contains biological semantics that should be treated with special algorithms. Endovascular coiling (or simply, coiling) is a primary treatment for intra-cranial aneurysm, which deploys a thin and detachable metal wire inside the aneurysm so as to prevent its rupture. Emerging evidence from medical research and clinical practice has suggested that the coil con- figuration inside the aneurysm plays a vital role in properly treating aneurysm and predicting its outcome.In this thesis, we mainly focus on developing algorithms for the above two types of applications. For the first area, we proposed two algorithms : 1) mining k-median graphs from chromosome association graphs, where each median graph is a representative structure of chromosome associations of a subset of the cells in the population; 2) finding rigid sub-structure patterns of chromosome topology structures, which can be viewed as 3D point-sets. Different from most of the existing models for pattern reconstruction (where each input point-set is often treated as a single structure), our model views each input point-set as a collection of k rigid substructures, and aims to extract similar rigid substructures from each input point-set to form k rigid clusters.For the second area, we propose a novel virtual coiling technique, called Ball Wind- ing, for generating deployable coil configuration with ensured blocking ability (for the first time). It can be used as an automatic tool for virtually simulating coiling before its implantation and thus optimizes such treatments."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/79355"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["computer science"],"dc:title":["Algorithmic Approaches for Determining Spatial Patterns in Several Biomedical Applications"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:16Z"}