{"id":"https://openalex.org/W3184483477","doi":"https://doi.org/10.2352/issn.2470-1173.2021.1.vda-331","title":"Volume Data Segmentation Using Visual Selection","display_name":"Volume Data Segmentation Using Visual Selection","publication_year":2021,"publication_date":"2021-01-18","ids":{"openalex":"https://openalex.org/W3184483477","doi":"https://doi.org/10.2352/issn.2470-1173.2021.1.vda-331","mag":"3184483477"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2021.1.vda-331","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2021.1.vda-331","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035404506","display_name":"Shyh\u2010Kuang Ueng","orcid":"https://orcid.org/0000-0002-9683-4987"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shyh-Kuang Ueng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5034843923","display_name":"Hsin\u2010Cheng Huang","orcid":"https://orcid.org/0000-0002-5613-349X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hsin-Cheng Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08304969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"1","first_page":"331","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6210505962371826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5659018754959106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.559339165687561},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.539236307144165},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5360719561576843},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43876031041145325},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3820432722568512}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6210505962371826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5659018754959106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.559339165687561},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.539236307144165},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5360719561576843},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43876031041145325},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3820432722568512},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2021.1.vda-331","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2021.1.vda-331","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2798121181","https://openalex.org/W4239607854","https://openalex.org/W2016805743","https://openalex.org/W4242592912","https://openalex.org/W435830328","https://openalex.org/W2087896742","https://openalex.org/W4205762803","https://openalex.org/W2328676785","https://openalex.org/W2535856026","https://openalex.org/W1989025965"],"abstract_inverted_index":{"Segmentation":[0],"is":[1,9,27,88,103,126],"usually":[2],"performed":[3],"in":[4,33,90,142],"the":[5,34,39,58,67,71,91,95,107,110,115],"spatial":[6],"domain":[7],"and":[8,17,44,61,79,133,145],"likely":[10],"hindered":[11],"by":[12,74],"similar":[13,131],"intensity,":[14],"intensity":[15,35,68,92],"inhomogeneity,":[16],"partial":[18],"volume":[19,54],"effect.":[20],"In":[21],"this":[22,76],"article,":[23],"a":[24,63,83,98,123,138,148],"visual-selection":[25],"method":[26,117],"proposed":[28,51,116],"to":[29,56,105],"carry":[30],"out":[31],"segmentation":[32,140],"space":[36],"such":[37],"that":[38,114],"aforementioned":[40],"difficulties":[41],"are":[42],"alleviated":[43],"better":[45],"results":[46,121],"can":[47],"be":[48],"produced.":[49],"The":[50],"procedure":[52],"utilizes":[53],"rendering":[55],"explore":[57],"input":[59],"data":[60,151],"builds":[62],"transfer":[64,77],"function,":[65],"encoding":[66],"distribution":[69],"of":[70,85,128],"target.":[72],"Then,":[73],"using":[75],"function":[78],"image":[80],"processing":[81],"techniques,":[82],"region":[84,100],"interest":[86],"(ROI)":[87],"constructed":[89],"field.":[93],"At":[94],"following":[96],"stage,":[97],"texture-based":[99],"growing":[101],"computation":[102],"conducted":[104],"extract":[106],"target":[108],"from":[109,147],"ROI.":[111],"Experiments":[112],"show":[113],"produces":[118],"high":[119],"quality":[120],"for":[122],"phantom":[124],"which":[125],"composed":[127],"plates":[129],"with":[130],"intensities":[132],"textures.":[134],"It":[135],"also":[136],"out-performs":[137],"traditional":[139],"system":[141],"separating":[143],"organs":[144],"tissues":[146],"torso":[149],"CT-scan":[150],"set.":[152]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
