{"id":"https://openalex.org/W2289603953","doi":"https://doi.org/10.1142/s0219467816500017","title":"Automatic Segmentation of Bones in X-ray Images Based on Entropy Measure","display_name":"Automatic Segmentation of Bones in X-ray Images Based on Entropy Measure","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2289603953","doi":"https://doi.org/10.1142/s0219467816500017","mag":"2289603953"},"language":"en","primary_location":{"id":"doi:10.1142/s0219467816500017","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467816500017","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-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/A5042807733","display_name":"Oishila Bandyopadhyay","orcid":"https://orcid.org/0000-0002-0348-371X"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Oishila Bandyopadhyay","raw_affiliation_strings":["Advanced Computing and Microelectronics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India"],"affiliations":[{"raw_affiliation_string":"Advanced Computing and Microelectronics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079139411","display_name":"Bhabatosh Chanda","orcid":"https://orcid.org/0009-0008-7648-6867"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bhabatosh Chanda","raw_affiliation_strings":["Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India"],"affiliations":[{"raw_affiliation_string":"Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067730042","display_name":"Bhargab B. Bhattacharya","orcid":"https://orcid.org/0000-0002-5890-2483"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Bhargab B. Bhattacharya","raw_affiliation_strings":["Advanced Computing and Microelectronics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India"],"affiliations":[{"raw_affiliation_string":"Advanced Computing and Microelectronics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042807733"],"corresponding_institution_ids":["https://openalex.org/I6498739"],"apc_list":null,"apc_paid":null,"fwci":1.503,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.87710407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"16","issue":"01","first_page":"1650001","last_page":"1650001"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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/T11363","display_name":"Dental Radiography and Imaging","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3504","display_name":"Oral Surgery"},"field":{"id":"https://openalex.org/fields/35","display_name":"Dentistry"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7708078622817993},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7208916544914246},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6938650608062744},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6027328968048096},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5534343123435974},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5510330200195312},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5375373959541321},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5187106728553772},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4732949137687683},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.468278169631958},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4277094900608063},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.41897106170654297},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21132910251617432}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7708078622817993},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7208916544914246},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6938650608062744},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6027328968048096},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5534343123435974},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5510330200195312},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5375373959541321},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5187106728553772},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4732949137687683},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.468278169631958},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4277094900608063},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.41897106170654297},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21132910251617432},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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:10.1142/s0219467816500017","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219467816500017","pdf_url":null,"source":{"id":"https://openalex.org/S60080701","display_name":"International Journal of Image and Graphics","issn_l":"0219-4678","issn":["0219-4678","1793-6756"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Image and Graphics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1911904603","https://openalex.org/W1966325234","https://openalex.org/W1979432452","https://openalex.org/W2002210570","https://openalex.org/W2002260165","https://openalex.org/W2008043556","https://openalex.org/W2034110104","https://openalex.org/W2035244546","https://openalex.org/W2051253644","https://openalex.org/W2062785607","https://openalex.org/W2074049473","https://openalex.org/W2078745075","https://openalex.org/W2081360103","https://openalex.org/W2085857202","https://openalex.org/W2094050562","https://openalex.org/W2097164998","https://openalex.org/W2104095591","https://openalex.org/W2108237140","https://openalex.org/W2118386984","https://openalex.org/W2119823327","https://openalex.org/W2121189958","https://openalex.org/W2129387542","https://openalex.org/W2133003941","https://openalex.org/W2133059825","https://openalex.org/W2133401603","https://openalex.org/W2135705692","https://openalex.org/W2145023731","https://openalex.org/W2145237807","https://openalex.org/W2148936972","https://openalex.org/W2157946140","https://openalex.org/W2158987937","https://openalex.org/W2170633497","https://openalex.org/W2323593827","https://openalex.org/W3108241563","https://openalex.org/W3206507930"],"related_works":["https://openalex.org/W1631910785","https://openalex.org/W2551390060","https://openalex.org/W2045391057","https://openalex.org/W1669643531","https://openalex.org/W2347731544","https://openalex.org/W1507266234","https://openalex.org/W2739874619","https://openalex.org/W2117664411","https://openalex.org/W2181351615","https://openalex.org/W2106595108"],"abstract_inverted_index":{"In":[0,126],"this":[1],"paper,":[2],"we":[3,134],"introduce":[4],"an":[5,14],"efficient":[6,108],"method":[7],"for":[8,73,105],"segmenting":[9],"the":[10,26,44,56,60,95,130,151,169,175,196,199],"bone":[11,27,180],"region":[12,122],"of":[13,25,39,49,59,76,91,94,110,114,132,150,177,198],"X-ray":[15,32,116,157],"image":[16,33],"from":[17,65,168],"its":[18,40],"surrounding":[19,45],"muscles":[20],"and":[21,51,107,123,188],"tissues.":[22],"Automated":[23],"segmentation":[24,85,183],"part":[28],"in":[29],"a":[30,35,82,89,111,136],"digital":[31],"is":[34],"challenging":[36],"problem":[37],"because":[38],"low":[41],"contrast":[42],"with":[43],"flesh.":[46],"The":[47],"presence":[48],"noise":[50],"spurious":[52],"edges":[53],"further":[54],"complicates":[55],"segmentation.":[57],"Most":[58],"existing":[61],"methods":[62],"either":[63],"suffer":[64],"noisy":[66],"contour":[67,141,152],"detection":[68],"or":[69],"need":[70],"training":[71],"samples":[72],"manual":[74],"tuning":[75],"certain":[77,147],"thresholding":[78],"parameters.":[79],"We":[80,172],"propose":[81,135],"fully":[83],"automated":[84],"technique,":[86],"which":[87],"utilizes":[88],"variant":[90],"entropy":[92,184],"measure":[93],"image.":[96],"This":[97],"scheme":[98],"has":[99],"been":[100],"shown":[101],"to":[102,128,163,202],"be":[103],"useful":[104],"fast":[106],"analysis":[109],"wide":[112],"class":[113],"human":[115],"images":[117,158,181],"including":[118],"skull,":[119],"chest,":[120],"pelvic":[121],"ortho-dental":[124],"zones.":[125],"order":[127],"quantify":[129],"quality":[131,176],"segmentation,":[133],"new":[137],"metric":[138],"called":[139],"average":[140],"distortion":[142],"index":[143],"(ACDI)":[144],"based":[145],"on":[146,155],"neighborhood":[148],"properties":[149],"pixels.":[153],"Experiments":[154],"several":[156,178],"reveal":[159],"encouraging":[160],"results":[161],"compared":[162],"other":[164],"approaches":[165],"as":[166],"evident":[167],"ACDI":[170],"metric.":[171],"also":[173],"re-validate":[174],"segmented":[179],"using":[182],"quantitative":[185],"assessment":[186],"(SEQA),":[187],"boundary-based":[189],"precision\u2013recall":[190],"profile.":[191],"All":[192],"three":[193],"metrics":[194],"establish":[195],"superiority":[197],"proposed":[200],"technique":[201],"prior":[203],"art.":[204]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}