{"id":"https://openalex.org/W2526653212","doi":"https://doi.org/10.1007/978-3-319-46726-9_27","title":"An Artificial Agent for Anatomical Landmark Detection in Medical Images","display_name":"An Artificial Agent for Anatomical Landmark Detection in Medical Images","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2526653212","doi":"https://doi.org/10.1007/978-3-319-46726-9_27","mag":"2526653212"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-46726-9_27","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-46726-9_27","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/978-3-319-46726-9_27","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113976165","display_name":"Florin C. Ghesu","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]},{"id":"https://openalex.org/I4210151799","display_name":"Siemens Healthcare (United States)","ror":"https://ror.org/054962n91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151799"]}],"countries":["DE","US"],"is_corresponding":true,"raw_author_name":"Florin C. Ghesu","raw_affiliation_strings":["Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA","Pattern Recognition Lab, Friedrich-Alexander-Universit\u00e4t, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210151799"]},{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander-Universit\u00e4t, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011888340","display_name":"Bogdan Georgescu","orcid":"https://orcid.org/0000-0001-5388-5699"},"institutions":[{"id":"https://openalex.org/I4210151799","display_name":"Siemens Healthcare (United States)","ror":"https://ror.org/054962n91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151799"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bogdan Georgescu","raw_affiliation_strings":["Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210151799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077640348","display_name":"Tommaso Mansi","orcid":"https://orcid.org/0000-0002-8342-4110"},"institutions":[{"id":"https://openalex.org/I4210151799","display_name":"Siemens Healthcare (United States)","ror":"https://ror.org/054962n91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151799"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tommaso Mansi","raw_affiliation_strings":["Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210151799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102875165","display_name":"Dominik Neumann","orcid":"https://orcid.org/0000-0003-2494-5124"},"institutions":[{"id":"https://openalex.org/I4210151799","display_name":"Siemens Healthcare (United States)","ror":"https://ror.org/054962n91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151799"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dominik Neumann","raw_affiliation_strings":["Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210151799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058662444","display_name":"Joachim Hornegger","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Joachim Hornegger","raw_affiliation_strings":["Pattern Recognition Lab, Friedrich-Alexander-Universit\u00e4t, Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Pattern Recognition Lab, Friedrich-Alexander-Universit\u00e4t, Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012751147","display_name":"Dorin Comaniciu","orcid":"https://orcid.org/0000-0002-5238-8647"},"institutions":[{"id":"https://openalex.org/I4210151799","display_name":"Siemens Healthcare (United States)","ror":"https://ror.org/054962n91","country_code":"US","type":"company","lineage":["https://openalex.org/I4210151799"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dorin Comaniciu","raw_affiliation_strings":["Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA"],"affiliations":[{"raw_affiliation_string":"Medical Imaging Technologies, Siemens Healthineers, Princeton, New Jersey, USA","institution_ids":["https://openalex.org/I4210151799"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5113976165"],"corresponding_institution_ids":["https://openalex.org/I181369854","https://openalex.org/I4210151799"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":6.0052,"has_fulltext":false,"cited_by_count":148,"citation_normalized_percentile":{"value":0.97309864,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/T10052","display_name":"Medical Image Segmentation Techniques","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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.995199978351593,"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/computer-science","display_name":"Computer science","score":0.8171472549438477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8157012462615967},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.7976438999176025},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6788889169692993},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.540935218334198},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4877258241176605},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4662885367870331},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45979544520378113},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.45882272720336914},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.452372670173645},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4444209039211273},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44189831614494324},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44186586141586304},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41645684838294983},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4124813973903656},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3510935604572296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15429645776748657}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8171472549438477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8157012462615967},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.7976438999176025},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6788889169692993},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.540935218334198},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4877258241176605},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4662885367870331},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45979544520378113},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.45882272720336914},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.452372670173645},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4444209039211273},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44189831614494324},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44186586141586304},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41645684838294983},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4124813973903656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3510935604572296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15429645776748657},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-46726-9_27","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-46726-9_27","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-319-46726-9_27","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-319-46726-9_27","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W60493759","https://openalex.org/W1515851193","https://openalex.org/W1557517019","https://openalex.org/W1583431585","https://openalex.org/W1595483645","https://openalex.org/W2122410182","https://openalex.org/W2145339207","https://openalex.org/W2179488730","https://openalex.org/W2229677101","https://openalex.org/W2318872361","https://openalex.org/W2399244897"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W4243161226","https://openalex.org/W2950647290","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W1968481813","https://openalex.org/W2392886708"],"abstract_inverted_index":{"Fast":[0],"and":[1,25,32,90,139,168,177,186],"robust":[2],"detection":[3,192],"of":[4,18,37,52,109,132,175,194,202],"anatomical":[5,43,149],"structures":[6],"or":[7,50,59,68],"pathologies":[8],"represents":[9],"a":[10,41,74,79,96,130],"fundamental":[11],"task":[12,99],"in":[13,173],"medical":[14],"image":[15],"analysis.":[16],"Most":[17],"the":[19,35,56,60,87,91,107,135,147,157,200,206],"current":[20],"solutions":[21],"are":[22],"however":[23],"suboptimal":[24],"unconstrained":[26],"by":[27,83],"learning":[28,76,111,115,167,170],"an":[29,101,203],"appearance":[30,57,89],"model":[31,58],"exhaustively":[33,155],"scanning":[34,156],"space":[36],"parameters":[38],"to":[39,55,146,154],"detect":[40],"specific":[42],"structure.":[44],"In":[45],"addition,":[46],"typical":[47],"feature":[48,119],"computation":[49],"estimation":[51],"meta-parameters":[53],"related":[54],"search":[61,93],"strategy,":[62],"is":[63],"based":[64],"on":[65,179],"local":[66],"criteria":[67],"predefined":[69],"approximation":[70],"schemes.":[71],"We":[72,125],"propose":[73],"new":[75],"method":[77,105,162],"following":[78],"fundamentally":[80],"different":[81],"paradigm":[82],"simultaneously":[84],"modeling":[85],"both":[86,172],"object":[88,204],"parameter":[92],"strategy":[94],"as":[95,152],"unified":[97],"behavioral":[98],"for":[100],"artificial":[102],"agent.":[103],"The":[104,161],"combines":[106],"advantages":[108],"behavior":[110],"achieved":[112,121],"through":[113,122],"reinforcement":[114],"with":[116],"effective":[117],"hierarchical":[118],"extraction":[120],"deep":[123,169],"learning.":[124],"show":[126],"that":[127,144],"given":[128],"only":[129],"sequence":[131],"annotated":[133],"images,":[134,183,189],"agent":[136],"can":[137],"automatically":[138],"strategically":[140],"learn":[141],"optimal":[142],"paths":[143],"converge":[145],"sought":[148],"landmark":[150],"location":[151],"opposed":[153],"entire":[158],"solution":[159],"space.":[160],"significantly":[163],"outperforms":[164],"state-of-the-art":[165],"machine":[166],"approaches":[171],"terms":[174],"accuracy":[176],"speed":[178],"2D":[180,184],"magnetic":[181],"resonance":[182],"ultrasound":[185],"3D":[187],"CT":[188],"achieving":[190],"average":[191],"errors":[193],"1-2":[195],"pixels,":[196],"while":[197],"also":[198],"recognizing":[199],"absence":[201],"from":[205],"image.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}