{"id":"https://openalex.org/W4327520721","doi":"https://doi.org/10.1145/3576938.3576940","title":"3D Binary Lesion Mask Parsing","display_name":"3D Binary Lesion Mask Parsing","publication_year":2022,"publication_date":"2022-11-10","ids":{"openalex":"https://openalex.org/W4327520721","doi":"https://doi.org/10.1145/3576938.3576940"},"language":"en","primary_location":{"id":"doi:10.1145/3576938.3576940","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3576938.3576940","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Digital Medicine and Image Processing","raw_type":"proceedings-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/A5025130564","display_name":"Yi-Qing Wang","orcid":"https://orcid.org/0000-0001-9641-9399"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi-Qing Wang","raw_affiliation_strings":["IBM Watson Health Imaging, France"],"raw_orcid":"https://orcid.org/0000-0001-9641-9399","affiliations":[{"raw_affiliation_string":"IBM Watson Health Imaging, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052114074","display_name":"Giovanni Palma","orcid":"https://orcid.org/0000-0002-1704-2317"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Giovanni Palma","raw_affiliation_strings":["IBM Watson Health Imaging, France"],"raw_orcid":"https://orcid.org/0000-0002-1704-2317","affiliations":[{"raw_affiliation_string":"IBM Watson Health Imaging, France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025130564"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15866491,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9855999946594238,"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":0.9855999946594238,"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/T10073","display_name":"Hepatocellular Carcinoma Treatment and Prognosis","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2721","display_name":"Hepatology"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9724000096321106,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.8403050899505615},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7700141668319702},{"id":"https://openalex.org/keywords/lesion","display_name":"Lesion","score":0.7092626094818115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6605654954910278},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.6335884928703308},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6133432984352112},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5406477451324463},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.44277745485305786},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37310218811035156},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36804431676864624},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.27049997448921204},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1761784553527832},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07114621996879578}],"concepts":[{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.8403050899505615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7700141668319702},{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.7092626094818115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6605654954910278},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.6335884928703308},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6133432984352112},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5406477451324463},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.44277745485305786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37310218811035156},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36804431676864624},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.27049997448921204},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1761784553527832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07114621996879578},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3576938.3576940","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3576938.3576940","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Digital Medicine and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W287611495","https://openalex.org/W2131006320","https://openalex.org/W2141461755","https://openalex.org/W2897666251","https://openalex.org/W2946046356","https://openalex.org/W2964227007","https://openalex.org/W2965669393","https://openalex.org/W3159065509","https://openalex.org/W3176031707","https://openalex.org/W3204000660"],"related_works":["https://openalex.org/W579810227","https://openalex.org/W2952780262","https://openalex.org/W2979495269","https://openalex.org/W2392917763","https://openalex.org/W2083429127","https://openalex.org/W2358855848","https://openalex.org/W2142145894","https://openalex.org/W2033808215","https://openalex.org/W2359307945","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Liver":[0],"lesion":[1,25,48,58,104],"segmentation":[2],"is":[3,35,73],"a":[4,66,97,124],"key":[5],"module":[6],"for":[7,27,76,100],"an":[8,107],"automated":[9],"liver":[10],"disease":[11],"diagnosis":[12],"system.":[13],"Numerous":[14],"methods":[15],"have":[16],"been":[17],"developed":[18],"recently":[19],"to":[20,38,41,52,109],"produce":[21],"accurate":[22],"3D":[23,69,102,119],"binary":[24,103],"masks":[26,45,105],"CT":[28],"scans.":[29],"From":[30],"the":[31,63,87],"clinical":[32],"perspective,":[33],"it":[34,80],"thus":[36],"important":[37],"be":[39],"able":[40],"correctly":[42],"parse":[43],"these":[44],"into":[46],"separate":[47],"instances":[49],"in":[50,86],"order":[51],"enable":[53],"downstream":[54],"applications":[55],"such":[56],"as":[57],"tracking":[59],"and":[60,106],"characterization.":[61],"For":[62],"lack":[64],"of":[65,89,127],"better":[67],"alternative,":[68],"connected":[70,120],"component":[71,121],"analysis":[72,122],"often":[74],"used":[75],"this":[77,93],"task,":[78],"though":[79],"does":[81],"not":[82],"always":[83],"work,":[84],"especially":[85],"presence":[88],"confluent":[90],"lesions.":[91],"In":[92],"paper,":[94],"we":[95],"propose":[96],"new":[98],"method":[99,117],"parsing":[101],"approach":[108],"evaluating":[110],"its":[111],"performance.":[112],"We":[113],"show":[114],"that":[115],"our":[116],"outperforms":[118],"on":[123],"large":[125],"collection":[126],"annotated":[128],"portal-venous":[129],"phase":[130],"studies.":[131]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
