{"id":"https://openalex.org/W4389983376","doi":"https://doi.org/10.48550/arxiv.2312.10585","title":"ESDMR-Net: A Lightweight Network With Expand-Squeeze and Dual Multiscale Residual Connections for Medical Image Segmentation","display_name":"ESDMR-Net: A Lightweight Network With Expand-Squeeze and Dual Multiscale Residual Connections for Medical Image Segmentation","publication_year":2023,"publication_date":"2023-12-17","ids":{"openalex":"https://openalex.org/W4389983376","doi":"https://doi.org/10.48550/arxiv.2312.10585"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2312.10585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.10585","pdf_url":"https://arxiv.org/pdf/2312.10585","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2312.10585","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070815655","display_name":"Mohammad A. U. Khan","orcid":"https://orcid.org/0000-0003-2640-3986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khan, Tariq M","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014712593","display_name":"Syed S. Naqvi","orcid":"https://orcid.org/0000-0002-6335-3538"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naqvi, Syed S.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5023548565","display_name":"Erik Meijering","orcid":"https://orcid.org/0000-0001-8015-8358"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meijering, Erik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9973000288009644,"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":0.9973000288009644,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9972000122070312,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9969000220298767,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8016531467437744},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.624610185623169},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5315506458282471},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5041865110397339},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5033459067344666},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49426937103271484},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4852418899536133},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.4740728437900543},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4584479033946991},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.44742751121520996},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4443415403366089},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4352276921272278},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4099721908569336},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.3522222638130188},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1971941590309143}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8016531467437744},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.624610185623169},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5315506458282471},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5041865110397339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5033459067344666},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49426937103271484},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4852418899536133},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.4740728437900543},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4584479033946991},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.44742751121520996},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4443415403366089},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4352276921272278},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4099721908569336},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3522222638130188},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1971941590309143},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2312.10585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.10585","pdf_url":"https://arxiv.org/pdf/2312.10585","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2312.10585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2312.10585","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2312.10585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2312.10585","pdf_url":"https://arxiv.org/pdf/2312.10585","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389983376.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2045155990","https://openalex.org/W4313163053","https://openalex.org/W2949601986","https://openalex.org/W4293226380","https://openalex.org/W4300973204","https://openalex.org/W3045811229","https://openalex.org/W4390516098","https://openalex.org/W2788972299","https://openalex.org/W4301867275","https://openalex.org/W2790610275"],"abstract_inverted_index":{"Segmentation":[0],"is":[1,77,83],"an":[2,21,69],"important":[3],"task":[4],"in":[5,23,45,208],"a":[6,78,238],"wide":[7],"range":[8],"of":[9,26,54,103,128,175,204,223,240,246],"computer":[10],"vision":[11],"applications,":[12],"including":[13],"medical":[14,27],"image":[15,28],"analysis.":[16],"Recent":[17],"years":[18],"have":[19],"seen":[20],"increase":[22],"the":[24,55,101,129,137,145,149,157,173,190,196,228],"complexity":[25],"segmentation":[29,150,169],"approaches":[30,57],"based":[31],"on":[32,47,96,216],"sophisticated":[33],"convolutional":[34,80],"neural":[35],"network":[36,74,81,158],"architectures.":[37],"This":[38,66,193],"progress":[39],"has":[40],"led":[41],"to":[42,136,162,167,198],"incremental":[43],"enhancements":[44],"performance":[46],"widely":[48],"recognised":[49],"benchmark":[50],"datasets.":[51],"However,":[52],"most":[53],"existing":[56],"are":[58],"computationally":[59],"demanding,":[60],"which":[61,76,142,165],"limits":[62],"their":[63],"practical":[64],"applicability.":[65],"paper":[67],"presents":[68],"expand-squeeze":[70],"dual":[71,184],"multiscale":[72,98,133,185],"residual":[73,186],"(ESDMR-Net),":[75],"fully":[79],"that":[82],"particularly":[84],"well-suited":[85],"for":[86,148],"resource-constrained":[87],"computing":[88],"hardware":[89],"such":[90],"as":[91],"mobile":[92],"devices.":[93],"ESDMR-Net":[94,111],"focuses":[95],"extracting":[97],"features,":[99],"enabling":[100],"learning":[102],"contextual":[104],"dependencies":[105],"among":[106],"semantically":[107],"distinct":[108,221],"features.":[109],"The":[110,120,152],"architecture":[112],"allows":[113],"dual-stream":[114],"information":[115,134,147,176],"flow":[116,174],"within":[117],"encoder-decoder":[118],"pairs.":[119],"expansion":[121],"operation":[122,139],"(depthwise":[123],"separable":[124],"convolution)":[125],"makes":[126],"all":[127],"rich":[130],"features":[131,200],"with":[132,237],"available":[135],"squeeze":[138],"(bottleneck":[140],"layer),":[141],"then":[143],"extracts":[144],"necessary":[146],"task.":[151],"Expand-Squeeze":[153],"(ES)":[154],"block":[155],"helps":[156],"pay":[159],"more":[160,209],"attention":[161],"under-represented":[163],"classes,":[164],"contributes":[166],"improved":[168],"accuracy.":[170],"To":[171],"enhance":[172],"across":[177],"multiple":[178],"resolutions":[179],"or":[180,242],"scales,":[181],"we":[182],"integrated":[183],"(DMR)":[187],"blocks":[188],"into":[189],"skip":[191],"connection.":[192],"integration":[194],"enables":[195],"decoder":[197],"access":[199],"from":[201,219],"various":[202],"levels":[203],"abstraction,":[205],"ultimately":[206],"resulting":[207],"comprehensive":[210],"feature":[211],"representations.":[212],"We":[213],"present":[214],"experiments":[215],"seven":[217],"datasets":[218],"five":[220],"examples":[222],"applications.":[224],"Our":[225],"model":[226],"achieved":[227],"best":[229],"results":[230],"despite":[231],"having":[232],"significantly":[233],"fewer":[234],"trainable":[235],"parameters,":[236],"reduction":[239],"two":[241],"even":[243],"three":[244],"orders":[245],"magnitude.":[247]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}
