{"id":"https://openalex.org/W2516301441","doi":"https://doi.org/10.1109/icip.2016.7532776","title":"Detection of the midsagittal plane in MR images using a sheetness measure from eigenanalysis of local 3D phase congruency responses","display_name":"Detection of the midsagittal plane in MR images using a sheetness measure from eigenanalysis of local 3D phase congruency responses","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2516301441","doi":"https://doi.org/10.1109/icip.2016.7532776","mag":"2516301441"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532776","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/A5027699113","display_name":"Ricardo J. Ferrari","orcid":"https://orcid.org/0000-0003-1197-2553"},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Ricardo J. Ferrari","raw_affiliation_strings":["BipGroup - Department of Computer Science, Federal University of S\u00e3o Carlos, S\u00e3o Carlos, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"BipGroup - Department of Computer Science, Federal University of S\u00e3o Carlos, S\u00e3o Carlos, SP, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060097760","display_name":"Carlos Henrique Villa Pinto","orcid":"https://orcid.org/0000-0002-3599-7811"},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Carlos H. Villa Pinto","raw_affiliation_strings":["BipGroup - Department of Computer Science, Federal University of S\u00e3o Carlos, S\u00e3o Carlos, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"BipGroup - Department of Computer Science, Federal University of S\u00e3o Carlos, S\u00e3o Carlos, SP, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080799013","display_name":"Camilo Aparecido Ferri Moreira","orcid":"https://orcid.org/0000-0003-0166-0206"},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Camilo A. Ferri Moreira","raw_affiliation_strings":["BipGroup - Department of Computer Science, Federal University of S\u00e3o Carlos, S\u00e3o Carlos, SP, Brazil"],"affiliations":[{"raw_affiliation_string":"BipGroup - Department of Computer Science, Federal University of S\u00e3o Carlos, S\u00e3o Carlos, SP, Brazil","institution_ids":["https://openalex.org/I177909021"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027699113"],"corresponding_institution_ids":["https://openalex.org/I177909021"],"apc_list":null,"apc_paid":null,"fwci":0.501,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.7254099,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"2335","last_page":"2339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.998199999332428,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7488240003585815},{"id":"https://openalex.org/keywords/phase-congruency","display_name":"Phase congruency","score":0.6941627264022827},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.661209225654602},{"id":"https://openalex.org/keywords/sagittal-plane","display_name":"Sagittal plane","score":0.6293800473213196},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6207724809646606},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.466054767370224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4619700312614441},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45326516032218933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4446728825569153},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4109204113483429},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3429507315158844},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10624974966049194}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7488240003585815},{"id":"https://openalex.org/C2777316791","wikidata":"https://www.wikidata.org/wiki/Q17105246","display_name":"Phase congruency","level":3,"score":0.6941627264022827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.661209225654602},{"id":"https://openalex.org/C178910020","wikidata":"https://www.wikidata.org/wiki/Q2211994","display_name":"Sagittal plane","level":2,"score":0.6293800473213196},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6207724809646606},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.466054767370224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4619700312614441},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45326516032218933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4446728825569153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4109204113483429},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3429507315158844},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10624974966049194},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532776","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/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1962010357","https://openalex.org/W1969532210","https://openalex.org/W1983024748","https://openalex.org/W1984712654","https://openalex.org/W1985550033","https://openalex.org/W2002405358","https://openalex.org/W2021877856","https://openalex.org/W2024520703","https://openalex.org/W2027627969","https://openalex.org/W2050236018","https://openalex.org/W2051725640","https://openalex.org/W2071460053","https://openalex.org/W2101689475","https://openalex.org/W2123532216","https://openalex.org/W2132782737","https://openalex.org/W2134495751","https://openalex.org/W2135291614","https://openalex.org/W2147245915","https://openalex.org/W6640974819","https://openalex.org/W6642824774","https://openalex.org/W6663172823"],"related_works":["https://openalex.org/W2351341560","https://openalex.org/W3027020613","https://openalex.org/W3187450193","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2020537709","https://openalex.org/W2892386716","https://openalex.org/W4306164210","https://openalex.org/W1998563493","https://openalex.org/W4313316311"],"abstract_inverted_index":{"The":[0],"midsagittal":[1],"plane":[2,88],"(MSP)":[3],"separates":[4],"the":[5,31,34,69,85,92,98,109,119,152,158],"cerebrum":[6],"into":[7],"left":[8],"and":[9,12,131,134,145,160],"right":[10],"hemispheres":[11],"its":[13],"detection":[14,32],"has":[15,136],"a":[16,43,79,114,165],"number":[17],"of":[18,33,49,52,55,97,108,157],"useful":[19],"applications":[20],"in":[21,36,78],"brain":[22,147],"image":[23],"processing.":[24],"We":[25],"propose":[26],"an":[27],"automatic":[28],"technique":[29,112,122],"for":[30,142],"MSP":[35],"magnetic":[37],"resonance":[38],"(MR)":[39],"images":[40,128],"that":[41],"uses":[42,113],"sheetness":[44],"measure":[45,116],"obtained":[46],"from":[47],"eigenanalysis":[48],"local":[50],"matrix":[51],"second-order":[53],"moments":[54],"3D":[56],"phase":[57],"congruency":[58],"responses":[59],"to":[60,66,68,83,117,125,138,164],"determine":[61],"those":[62],"voxels":[63],"most":[64,96],"likely":[65],"belong":[67],"MSP.":[70,120],"A":[71],"weighted":[72],"least-squares":[73],"fitting":[74,87],"algorithm":[75],"is":[76],"used":[77],"coarse-to-fine":[80],"iterative":[81],"manner":[82],"find":[84,118],"best":[86],"(the":[89],"MSP)":[90],"through":[91],"selected":[93],"voxels.":[94],"Unlike":[95],"proposed":[99],"approaches,":[100],"which":[101],"are":[102],"mainly":[103],"based":[104],"on":[105],"symmetric":[106],"measures":[107],"brain,":[110],"our":[111],"direct":[115],"Our":[121],"was":[123],"applied":[124],"202":[126],"MR":[127],"(40":[129],"clinical":[130],"162":[132],"synthetic)":[133],"it":[135],"shown":[137],"be":[139],"very":[140],"effective":[141],"both":[143],"symmetrical":[144],"asymmetrical":[146],"images.":[148],"Quantitative":[149],"assessment,":[150],"using":[151],"angle":[153,168],"between":[154],"unit":[155],"normals":[156],"detected":[159],"reference":[161],"MSPs,":[162],"yielded":[163],"mean":[166],"absolute":[167],"value":[169],"bellow":[170],"0.5\u00b0.":[171]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}