{"id":"https://openalex.org/W7124257054","doi":"https://doi.org/10.3390/a19010072","title":"ZechariahNet: A Novel Method of MS Lesion Diagnosis Through MRI Images by the Combination of C-LSTM and 3D CNN Algorithms","display_name":"ZechariahNet: A Novel Method of MS Lesion Diagnosis Through MRI Images by the Combination of C-LSTM and 3D CNN Algorithms","publication_year":2026,"publication_date":"2026-01-15","ids":{"openalex":"https://openalex.org/W7124257054","doi":"https://doi.org/10.3390/a19010072"},"language":"en","primary_location":{"id":"doi:10.3390/a19010072","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19010072","pdf_url":"https://www.mdpi.com/1999-4893/19/1/72/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/19/1/72/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123063288","display_name":"Mahshid Dehghanpour","orcid":null},"institutions":[{"id":"https://openalex.org/I176861719","display_name":"University of Shahrood","ror":"https://ror.org/00yqvtm78","country_code":"IR","type":"education","lineage":["https://openalex.org/I176861719"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mahshid Dehghanpour","raw_affiliation_strings":["Faculty of Computer Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computer Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran","institution_ids":["https://openalex.org/I176861719"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053910791","display_name":"Mansoor Fateh","orcid":"https://orcid.org/0000-0003-2133-3480"},"institutions":[{"id":"https://openalex.org/I176861719","display_name":"University of Shahrood","ror":"https://ror.org/00yqvtm78","country_code":"IR","type":"education","lineage":["https://openalex.org/I176861719"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mansoor Fateh","raw_affiliation_strings":["Faculty of Computer Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran"],"raw_orcid":"https://orcid.org/0000-0003-2133-3480","affiliations":[{"raw_affiliation_string":"Faculty of Computer Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran","institution_ids":["https://openalex.org/I176861719"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079094382","display_name":"Zeynab Mohammadpoory","orcid":null},"institutions":[{"id":"https://openalex.org/I176861719","display_name":"University of Shahrood","ror":"https://ror.org/00yqvtm78","country_code":"IR","type":"education","lineage":["https://openalex.org/I176861719"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Zeynab Mohammadpoory","raw_affiliation_strings":["Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran","institution_ids":["https://openalex.org/I176861719"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010489255","display_name":"Saideh Ferdowsi","orcid":"https://orcid.org/0000-0002-8887-0339"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saideh Ferdowsi","raw_affiliation_strings":["School of Mathematics, Statistics and Actuarial Science, University of Essex, Colchester CO4 3SQ, UK"],"raw_orcid":"https://orcid.org/0000-0002-8887-0339","affiliations":[{"raw_affiliation_string":"School of Mathematics, Statistics and Actuarial Science, University of Essex, Colchester CO4 3SQ, UK","institution_ids":["https://openalex.org/I110002522"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":13.616,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.95206537,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"19","issue":"1","first_page":"72","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10137","display_name":"Multiple Sclerosis Research Studies","score":0.5051000118255615,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10137","display_name":"Multiple Sclerosis Research Studies","score":0.5051000118255615,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.20819999277591705,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.06430000066757202,"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/segmentation","display_name":"Segmentation","score":0.7056999802589417},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6184999942779541},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.5817000269889832},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5580000281333923},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.554099977016449},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5011000037193298},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43320000171661377},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.4156999886035919}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8112000226974487},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7056999802589417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.657800018787384},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6184999942779541},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.5817000269889832},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5580000281333923},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.554099977016449},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43320000171661377},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.412200003862381},{"id":"https://openalex.org/C2780640218","wikidata":"https://www.wikidata.org/wiki/Q8277","display_name":"Multiple sclerosis","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3898000121116638},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.388700008392334},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32359999418258667},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C3019831412","wikidata":"https://www.wikidata.org/wiki/Q5778278","display_name":"Fully automatic","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C2991673738","wikidata":"https://www.wikidata.org/wiki/Q5062122","display_name":"Brain disease","level":3,"score":0.25220000743865967}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a19010072","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19010072","pdf_url":"https://www.mdpi.com/1999-4893/19/1/72/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:20687af8d5d9493d8a523eecbbf2e52c","is_oa":true,"landing_page_url":"https://doaj.org/article/20687af8d5d9493d8a523eecbbf2e52c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 19, Iss 1, p 72 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a19010072","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a19010072","pdf_url":"https://www.mdpi.com/1999-4893/19/1/72/pdf","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7402586340904236,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7124257054.pdf","grobid_xml":"https://content.openalex.org/works/W7124257054.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2332066482","https://openalex.org/W2549139847","https://openalex.org/W2575552683","https://openalex.org/W2900299818","https://openalex.org/W3011743383","https://openalex.org/W3161761924","https://openalex.org/W3206607677","https://openalex.org/W4220658327","https://openalex.org/W4283692706","https://openalex.org/W4293089973","https://openalex.org/W4312084109","https://openalex.org/W4320525814","https://openalex.org/W4324128823","https://openalex.org/W4377565370","https://openalex.org/W4388177718","https://openalex.org/W4392720098","https://openalex.org/W4401751883","https://openalex.org/W4404161210","https://openalex.org/W4404609244","https://openalex.org/W4406238099","https://openalex.org/W4406351244","https://openalex.org/W4407295962","https://openalex.org/W4409247668","https://openalex.org/W4410774500","https://openalex.org/W4412467872","https://openalex.org/W4414087060","https://openalex.org/W4414347552","https://openalex.org/W4416782302","https://openalex.org/W7117976717"],"related_works":[],"abstract_inverted_index":{"In":[0],"light":[1],"of":[2,6,15,62,155],"the":[3,7,59,65,120,125,130],"growing":[4],"prevalence":[5],"autoimmune":[8],"disease":[9],"multiple":[10],"sclerosis":[11],"(MS),":[12],"accurate":[13],"detection":[14],"MS":[16,39,63],"lesions":[17,40],"in":[18,29,68],"brain":[19,43],"magnetic":[20],"resonance":[21],"imaging":[22],"(MRI)":[23],"images":[24],"plays":[25],"a":[26,77,96,150],"critical":[27],"role":[28],"assisting":[30],"neurologists":[31],"with":[32],"timely":[33],"diagnosis.":[34],"The":[35],"high":[36],"similarity":[37,152],"between":[38],"and":[41,90,112,114,122,137],"normal":[42],"tissues,":[44],"however,":[45],"makes":[46],"this":[47,69],"task":[48],"particularly":[49],"challenging.":[50],"Although":[51],"numerous":[52],"deep-learning-based":[53],"approaches":[54],"have":[55],"been":[56],"proposed":[57,126],"for":[58,133],"automatic":[60],"segmentation":[61,144],"lesions,":[64],"method":[66],"presented":[67],"study":[70],"has":[71],"achieved":[72],"superior":[73],"results.":[74],"ZechariahNet":[75,147],"is":[76],"U-Net-based":[78],"architecture":[79],"that":[80],"integrates":[81],"transition":[82],"down":[83],"blocks,":[84,87,89],"squeeze-attention":[85],"(SA)":[86],"dense":[88],"Convolutional":[91],"LSTM":[92],"(C-LSTM)":[93],"blocks":[94],"within":[95],"3D":[97],"CNN":[98],"framework.":[99],"By":[100],"jointly":[101],"exploiting":[102],"spatial\u2013temporal":[103],"information":[104],"from":[105],"three":[106],"consecutive":[107],"MRI":[108],"slices":[109],"(previous,":[110],"current,":[111],"subsequent)":[113],"strategically":[115],"applying":[116],"C-LSTM":[117],"modules":[118],"across":[119],"encoder":[121],"decoder":[123],"paths,":[124],"model":[127],"effectively":[128],"captures":[129],"neighborhood":[131],"dependencies":[132],"enhanced":[134],"feature":[135],"extraction":[136],"reconstruction.":[138],"These":[139],"architectural":[140],"innovations":[141],"significantly":[142],"improve":[143],"accuracy,":[145],"enabling":[146],"to":[148],"achieve":[149],"dice":[151],"coefficient":[153],"(DSC)":[154],"84.72%,":[156],"outperforming":[157],"existing":[158],"state-of-the-art":[159],"methods.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-16T00:00:00"}
