{"id":"https://openalex.org/W2904116886","doi":"https://doi.org/10.1145/3368555.3384462","title":"Fast learning-based registration of sparse 3D clinical images","display_name":"Fast learning-based registration of sparse 3D clinical images","publication_year":2020,"publication_date":"2020-03-20","ids":{"openalex":"https://openalex.org/W2904116886","doi":"https://doi.org/10.1145/3368555.3384462","mag":"2904116886"},"language":"en","primary_location":{"id":"doi:10.1145/3368555.3384462","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3368555.3384462","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3368555.3384462","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Conference on Health, Inference, and Learning","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3368555.3384462","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kathleen Lewis","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Kathleen Lewis","raw_affiliation_strings":["MIT"],"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I4210109586"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Natalia S. Rost","orcid":null},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Natalia S. Rost","raw_affiliation_strings":["Harvard Medical School, MGH"],"affiliations":[{"raw_affiliation_string":"Harvard Medical School, MGH","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":null,"display_name":"John Guttag","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"John Guttag","raw_affiliation_strings":["MIT"],"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I4210109586"]}]},{"author_position":"last","author":{"id":null,"display_name":"Adrian V. Dalca","orcid":null},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adrian V. Dalca","raw_affiliation_strings":["MIT, Harvard Medical School, MGH"],"affiliations":[{"raw_affiliation_string":"MIT, Harvard Medical School, MGH","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210109586"],"apc_list":null,"apc_paid":null,"fwci":0.1963,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.46854121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"90","last_page":"98"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9897000193595886,"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/image-registration","display_name":"Image registration","score":0.5723000168800354},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4271000027656555},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3903000056743622},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38929998874664307},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.3743000030517578},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.361299991607666}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7631000280380249},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7038999795913696},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6579999923706055},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.5723000168800354},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4271000027656555},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3903000056743622},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.3743000030517578},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3077999949455261},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.2734000086784363}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3368555.3384462","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3368555.3384462","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3368555.3384462","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Conference on Health, Inference, and Learning","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1812.06932","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.06932","pdf_url":"https://arxiv.org/pdf/1812.06932","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3368555.3384462","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3368555.3384462","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3368555.3384462","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Conference on Health, Inference, and Learning","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6372360375","display_name":null,"funder_award_id":"R21AG050122","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904116886.pdf","grobid_xml":"https://content.openalex.org/works/W2904116886.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1511772490","https://openalex.org/W1901129140","https://openalex.org/W1970928383","https://openalex.org/W1987869189","https://openalex.org/W1998710995","https://openalex.org/W2007153649","https://openalex.org/W2065646479","https://openalex.org/W2089607952","https://openalex.org/W2102099319","https://openalex.org/W2103857226","https://openalex.org/W2113576511","https://openalex.org/W2118961645","https://openalex.org/W2119848633","https://openalex.org/W2136145485","https://openalex.org/W2145661921","https://openalex.org/W2155298532","https://openalex.org/W2158167845","https://openalex.org/W2165840723","https://openalex.org/W2170167891","https://openalex.org/W2172210950","https://openalex.org/W2604920239","https://openalex.org/W2608822622","https://openalex.org/W2891631795","https://openalex.org/W2963196212","https://openalex.org/W4241074797"],"related_works":[],"abstract_inverted_index":{"We":[0,79,120],"introduce":[1],"SparseVM,":[2,85],"a":[3,27,81,125,134],"method":[4,109,123],"that":[5,86],"registers":[6],"clinical-quality":[7],"3D":[8],"MR":[9],"scans":[10,25,51],"both":[11],"faster":[12,94],"and":[13,90,132],"more":[14,88],"accurately":[15],"than":[16,95],"previously":[17],"possible.":[18],"Deformable":[19],"alignment,":[20],"or":[21,76],"registration,":[22],"of":[23,59,92,129,145],"clinical":[24,32,50,99,118],"is":[26,87,106,141],"fundamental":[28],"task":[29],"for":[30,41,68],"many":[31],"neuroscience":[33],"studies.":[34],"However,":[35],"most":[36,97],"registration":[37,83,100],"algorithms":[38],"are":[39,52,73],"designed":[40],"high-resolution":[42],"research-quality":[43,48,64],"scans.":[44,65],"In":[45],"contrast":[46],"to":[47,57,110,116],"scans,":[49],"often":[53],"sparse,":[54],"missing":[55],"up":[56],"86%":[58],"the":[60,96,107,146],"slices":[61],"available":[62,142],"in":[63],"Existing":[66],"methods":[67],"registering":[69,117],"these":[70],"sparse":[71,136],"images":[72],"either":[74],"inaccurate":[75],"extremely":[77],"slow.":[78],"present":[80],"learning-based":[82],"method,":[84],"accurate":[89,98],"orders":[91],"magnitude":[93],"methods.":[101],"To":[102],"our":[103,122],"knowledge,":[104],"it":[105],"first":[108],"use":[111],"deep":[112],"learning":[113],"specifically":[114],"tailored":[115],"images.":[119],"demonstrate":[121],"on":[124,133],"clinically-acquired":[126],"MRI":[127,137],"dataset":[128],"stroke":[130],"patients":[131],"simulated":[135],"dataset.":[138],"Our":[139],"code":[140],"as":[143],"part":[144],"VoxelMorph":[147],"package":[148],"at":[149],"http://voxelmorph.mit.edu.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2018-12-22T00:00:00"}
