{"id":"https://openalex.org/W4224992977","doi":"https://doi.org/10.1109/isbi52829.2022.9761519","title":"Semi-Supervised Segmentation of Mitochondria from Electron Microscopy Images Using Spatial Continuity","display_name":"Semi-Supervised Segmentation of Mitochondria from Electron Microscopy Images Using Spatial Continuity","publication_year":2022,"publication_date":"2022-03-28","ids":{"openalex":"https://openalex.org/W4224992977","doi":"https://doi.org/10.1109/isbi52829.2022.9761519"},"language":"en","primary_location":{"id":"doi:10.1109/isbi52829.2022.9761519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761519","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2206.02392","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076892263","display_name":"Yunpeng Xiao","orcid":"https://orcid.org/0000-0002-2846-3571"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yunpeng Xiao","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102757394","display_name":"Youpeng Zhao","orcid":"https://orcid.org/0000-0002-4610-3545"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youpeng Zhao","raw_affiliation_strings":["Chinese Academy of Sciences,National Laboratory of Pattern Recognition, Institute of Automation,Beijing,China,100190"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,National Laboratory of Pattern Recognition, Institute of Automation,Beijing,China,100190","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101911646","display_name":"Ge Yang","orcid":"https://orcid.org/0000-0002-5085-4261"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Yang","raw_affiliation_strings":["University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049","National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,School of Artificial Intelligence,Beijing,China,100049","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076892263"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.9864,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78756477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9886000156402588,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9883999824523926,"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":0.7485923171043396},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7101499438285828},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6814821362495422},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6279803514480591},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5914888978004456},{"id":"https://openalex.org/keywords/affine-transformation","display_name":"Affine transformation","score":0.5902562141418457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5690595507621765},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4755772650241852},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.464656263589859},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4362650513648987},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.42105215787887573},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3255500793457031},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22823894023895264},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12325209379196167},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09891942143440247},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.09151464700698853}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7485923171043396},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7101499438285828},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6814821362495422},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6279803514480591},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5914888978004456},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.5902562141418457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5690595507621765},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4755772650241852},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.464656263589859},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4362650513648987},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.42105215787887573},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3255500793457031},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22823894023895264},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12325209379196167},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09891942143440247},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.09151464700698853},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/isbi52829.2022.9761519","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi52829.2022.9761519","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2206.02392","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.02392","pdf_url":"https://arxiv.org/pdf/2206.02392","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":"pmh:oai:arXiv.org:2206.02392","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2206.02392","pdf_url":"https://arxiv.org/pdf/2206.02392","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"},"sustainable_development_goals":[{"score":0.5,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2100213115","https://openalex.org/W2131415852","https://openalex.org/W2156163116","https://openalex.org/W2163605009","https://openalex.org/W2464708700","https://openalex.org/W2616893597","https://openalex.org/W2620296437","https://openalex.org/W2775688034","https://openalex.org/W2792634584","https://openalex.org/W2803537647","https://openalex.org/W2899476650","https://openalex.org/W2962914239","https://openalex.org/W2979436723","https://openalex.org/W2997305317","https://openalex.org/W3026138667","https://openalex.org/W3093690432","https://openalex.org/W3101075246","https://openalex.org/W3125178388","https://openalex.org/W3209987414","https://openalex.org/W4287022992","https://openalex.org/W4287026023","https://openalex.org/W6639824700","https://openalex.org/W6684191040","https://openalex.org/W6800217721"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2251519152"],"abstract_inverted_index":{"Morphology":[0],"of":[1,13,26,49,57,65,95,123,140,149,174],"mitochondria":[2,14,89],"plays":[3],"critical":[4],"roles":[5],"in":[6,102],"mediating":[7],"their":[8,27,66,96,150],"physiological":[9],"functions.":[10],"Accurate":[11],"segmentation":[12],"from":[15,168],"3D":[16],"electron":[17],"microscopy":[18],"(EM)":[19],"images":[20,59],"is":[21,60,157],"essential":[22],"to":[23,114],"quantitative":[24],"characterization":[25],"morphology":[28,120],"at":[29,180],"the":[30,92,128],"nanometer":[31],"scale.":[32],"Fully":[33],"supervised":[34,143],"deep":[35,84],"learning":[36,85],"models":[37,144],"developed":[38],"for":[39,52,121],"this":[40,78,175],"task":[41],"achieve":[42],"excellent":[43],"performance":[44,136],"but":[45,145],"require":[46],"substantial":[47],"amounts":[48],"annotated":[50,151],"data":[51],"training.":[53],"However,":[54],"manual":[55],"annotation":[56],"EM":[58,169],"laborious":[61],"and":[62,71,99,105,117,159,172],"time-consuming":[63],"because":[64],"large":[67],"volumes,":[68],"limited":[69],"contrast,":[70],"low":[72],"signal-to-noise":[73],"ratios":[74],"(SNRs).":[75],"To":[76],"overcome":[77],"challenge,":[79],"we":[80],"propose":[81],"a":[82],"semi-supervised":[83,155],"model":[86,134,156],"that":[87,132,139],"segments":[88],"by":[90],"leveraging":[91],"spatial":[93],"continuity":[94],"structural,":[97],"morphological,":[98],"contextual":[100],"information":[101],"both":[103],"labeled":[104],"unlabeled":[106],"images.":[107,170],"We":[108],"use":[109],"random":[110],"piecewise":[111],"affine":[112],"transformation":[113],"synthesize":[115],"comprehensive":[116],"realistic":[118],"mitochondrial":[119],"augmentation":[122],"training":[124,152],"data.":[125,153],"Experiments":[126],"on":[127],"EPFL":[129],"dataset":[130],"show":[131],"our":[133],"achieves":[135],"similar":[137],"as":[138],"state-of-the-art":[141],"fully":[142],"requires":[146],"only":[147],"~20%":[148],"Our":[154],"versatile":[158],"can":[160],"also":[161],"accurately":[162],"segment":[163],"other":[164],"spatially":[165],"continuous":[166],"structures":[167],"Data":[171],"code":[173],"study":[176],"are":[177],"openly":[178],"accessible":[179],"https://github.com/cbmi-group/MPP.":[181]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
