{"id":"https://openalex.org/W2516732370","doi":"https://doi.org/10.1109/icip.2016.7532560","title":"Reduced-complexity image segmentation under parallel Markov Random Field formulation using graph partitioning","display_name":"Reduced-complexity image segmentation under parallel Markov Random Field formulation using graph partitioning","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2516732370","doi":"https://doi.org/10.1109/icip.2016.7532560","mag":"2516732370"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5059988741","display_name":"Talita Perciano","orcid":"https://orcid.org/0000-0002-2388-1803"},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"T. Perciano","raw_affiliation_strings":["Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA","institution_ids":["https://openalex.org/I148283060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050276927","display_name":"Daniela Ushizima","orcid":"https://orcid.org/0000-0002-7363-9468"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. M. Ushizima","raw_affiliation_strings":["University of California Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113461040","display_name":"E. Wes Bethel","orcid":null},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"E. W. Bethel","raw_affiliation_strings":["Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA","institution_ids":["https://openalex.org/I148283060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062072420","display_name":"Yariv Dror Mizrahi","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Y. D. Mizrahi","raw_affiliation_strings":["Mathematics Department, University of British Columbia, Canada"],"affiliations":[{"raw_affiliation_string":"Mathematics Department, University of British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015137668","display_name":"Dilworth Y. Parkinson","orcid":"https://orcid.org/0000-0002-1817-0716"},"institutions":[{"id":"https://openalex.org/I148283060","display_name":"Lawrence Berkeley National Laboratory","ror":"https://ror.org/02jbv0t02","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I148283060","https://openalex.org/I39565521"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Parkinson","raw_affiliation_strings":["Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Advanced Light Source, Lawrence Berkeley National Laboratory, Berkeley, CA, USA","institution_ids":["https://openalex.org/I148283060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038419345","display_name":"James A. Sethian","orcid":"https://orcid.org/0000-0002-7250-7789"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. A. Sethian","raw_affiliation_strings":["University of California Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5059988741"],"corresponding_institution_ids":["https://openalex.org/I148283060"],"apc_list":null,"apc_paid":null,"fwci":1.002,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83217816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"32","issue":null,"first_page":"1259","last_page":"1263"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9980999827384949,"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/markov-random-field","display_name":"Markov random field","score":0.7934015989303589},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7305970788002014},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6844475269317627},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6702015399932861},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5779165029525757},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5702610015869141},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4924558103084564},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.45395392179489136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44437310099601746},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4410404860973358},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.41399508714675903},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37655192613601685},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3372628092765808},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.289237380027771},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28055959939956665}],"concepts":[{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.7934015989303589},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7305970788002014},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6844475269317627},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6702015399932861},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5779165029525757},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5702610015869141},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4924558103084564},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.45395392179489136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44437310099601746},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4410404860973358},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.41399508714675903},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37655192613601685},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3372628092765808},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.289237380027771},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28055959939956665}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532560","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320337506","display_name":"Advanced Scientific Computing Research","ror":"https://ror.org/0012c7r22"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1554544485","https://openalex.org/W1590564964","https://openalex.org/W1974629471","https://openalex.org/W1999478155","https://openalex.org/W2001349183","https://openalex.org/W2016724224","https://openalex.org/W2025678883","https://openalex.org/W2030522583","https://openalex.org/W2069183996","https://openalex.org/W2080105297","https://openalex.org/W2082059038","https://openalex.org/W2101309634","https://openalex.org/W2105706220","https://openalex.org/W2114358147","https://openalex.org/W2121141217","https://openalex.org/W2121927366","https://openalex.org/W2134305927","https://openalex.org/W2143272559","https://openalex.org/W2148397114","https://openalex.org/W2152632881","https://openalex.org/W2168304982","https://openalex.org/W2479936045","https://openalex.org/W4213262319","https://openalex.org/W4297750044","https://openalex.org/W6633362792","https://openalex.org/W6684690731"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2387690017","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W2029983961","https://openalex.org/W4233585817","https://openalex.org/W2088651901","https://openalex.org/W2897997384"],"abstract_inverted_index":{"Markov":[0],"Random":[1],"Field":[2],"(MRF)":[3],"algorithms":[4],"are":[5],"powerful":[6],"tools":[7],"in":[8],"image":[9],"analysis":[10],"to":[11,23,33,86],"explore":[12],"contextual":[13],"information":[14],"of":[15,20,38],"data.":[16],"However,":[17],"the":[18,35,39,61,79,98],"application":[19],"these":[21],"methods":[22],"large":[24],"data":[25],"means":[26],"that":[27,47],"alternative":[28],"approaches":[29],"must":[30],"be":[31],"found":[32],"circumvent":[34],"NP-hard":[36],"complexity":[37,57],"MRF":[40],"optimization.":[41],"We":[42],"introduce":[43],"a":[44],"MRF-based":[45],"framework":[46],"overcomes":[48],"this":[49],"issue":[50],"by":[51],"using":[52],"graph":[53],"partitioning.":[54],"The":[55],"computational":[56],"is":[58,64],"decreased":[59],"as":[60],"optimization/parameter":[62],"estimation":[63],"executed":[65],"on":[66,78,97],"small":[67],"subgraphs.":[68],"PMRF":[69],"targets":[70],"3D":[71],"microCT":[72,99],"datasets,":[73],"but":[74],"we":[75],"include":[76],"evaluation":[77],"Berkeley":[80],"Segmentation":[81,95],"Dataset":[82],"(ranking":[83],"7th":[84],"place)":[85],"fully":[87],"compare":[88],"our":[89],"method":[90],"with":[91],"well-known":[92],"segmentation":[93],"algorithms.":[94],"results":[96],"datasets":[100],"achieve":[101],"precision":[102],"higher":[103],"than":[104],"95%.":[105]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}