{"id":"https://openalex.org/W2607015384","doi":"https://doi.org/10.1109/bhi.2017.7897247","title":"A tempo-spatial compressed sensing architecture for efficient high-throughput information acquisition in organs-on-a-chip","display_name":"A tempo-spatial compressed sensing architecture for efficient high-throughput information acquisition in organs-on-a-chip","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2607015384","doi":"https://doi.org/10.1109/bhi.2017.7897247","mag":"2607015384"},"language":"en","primary_location":{"id":"doi:10.1109/bhi.2017.7897247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi.2017.7897247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)","raw_type":"proceedings-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/A5100709117","display_name":"Chen Song","orcid":"https://orcid.org/0000-0002-0159-8150"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chen Song","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014929946","display_name":"Aosen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aosen Wang","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078406349","display_name":"Feng Lin","orcid":"https://orcid.org/0000-0001-5240-5200"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Lin","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062427245","display_name":"Ruogang Zhao","orcid":"https://orcid.org/0000-0002-5351-0843"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruogang Zhao","raw_affiliation_strings":["Department of Biomedical Engineering, University at Buffalo (SUNY), Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University at Buffalo (SUNY), Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044439388","display_name":"Zhanpeng Jin","orcid":"https://orcid.org/0000-0002-3020-3736"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhanpeng Jin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Binghamton University (SUNY), Binghamton, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Binghamton University (SUNY), Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035679293","display_name":"Wenyao Xu","orcid":"https://orcid.org/0000-0001-6444-9411"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenyao Xu","raw_affiliation_strings":["Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University at Buffalo (SUNY), Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100709117"],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":0.579,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7983934,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9995999932289124,"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.9995999932289124,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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/T11255","display_name":"Microfluidic and Bio-sensing Technologies","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7676927447319031},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.7329789400100708},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5690057277679443},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.48437079787254333},{"id":"https://openalex.org/keywords/data-acquisition","display_name":"Data acquisition","score":0.4721498489379883},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.45205163955688477},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4457835257053375},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4065053164958954},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.37765881419181824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28318843245506287},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.1368144452571869},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.12029018998146057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7676927447319031},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.7329789400100708},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5690057277679443},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.48437079787254333},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.4721498489379883},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.45205163955688477},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4457835257053375},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4065053164958954},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.37765881419181824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28318843245506287},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.1368144452571869},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.12029018998146057},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bhi.2017.7897247","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi.2017.7897247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1966440946","https://openalex.org/W2013520568","https://openalex.org/W2036648611","https://openalex.org/W2050998773","https://openalex.org/W2073715923","https://openalex.org/W2084423347","https://openalex.org/W2092680585","https://openalex.org/W2101675075","https://openalex.org/W2122548617","https://openalex.org/W2288046058","https://openalex.org/W2296269654","https://openalex.org/W2330214351","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2465351041","https://openalex.org/W1976264255"],"abstract_inverted_index":{"As":[0],"a":[1,17,26,88,158,169],"micro":[2],"engineered":[3],"biomimetic":[4],"system":[5,140],"to":[6,60,144],"replicate":[7],"key":[8],"functions":[9],"of":[10],"living":[11],"organs,":[12],"organs-on-a-chip":[13],"(OC)":[14],"technology":[15],"provides":[16],"high-throughput":[18],"model":[19],"for":[20,43,76,92],"investigating":[21],"complex":[22],"cell":[23],"interactions":[24],"with":[25,104,157],"high":[27],"temporal":[28,108],"and":[29,37,49,65,100,109,136,161],"spatial":[30,110],"resolution":[31],"in":[32,126],"biological":[33],"studies.":[34],"Typically,":[35],"microscopy":[36],"highspeed":[38],"video":[39],"cameras":[40],"are":[41,47],"used":[42],"data":[44],"acquisition,":[45],"which":[46,95],"expensive":[48],"bulky.":[50],"Recently,":[51],"compressed":[52],"sensing":[53,103],"(CS)":[54],"has":[55],"increasingly":[56],"attracted":[57],"attentions":[58],"due":[59],"its":[61],"extremely":[62],"low-complexity":[63],"structure":[64],"low":[66],"sampling":[67],"rate.":[68],"However,":[69],"there":[70],"is":[71],"no":[72],"CS":[73,86,90],"solution":[74],"tailored":[75],"tempo-spatial":[77,124],"information":[78],"acquisition.":[79],"In":[80],"this":[81,130],"paper,":[82],"we":[83,132,148],"propose":[84],"Tempo-Spatial":[85],"(TS-CS),":[87],"unified":[89],"architecture":[91,135],"OC":[93,127],"stream":[94],"achieves":[96],"significant":[97],"cost":[98],"reduction":[99],"truly":[101],"combines":[102],"compression":[105],"along":[106],"the":[107,139,145],"domains.":[111],"We":[112],"point":[113],"out":[114],"that":[115,150],"TS-CS":[116,134,151],"can":[117,162],"consistently":[118],"achieve":[119,163],"better":[120,154],"performance":[121],"by":[122],"exploiting":[123],"compressibility":[125],"data.":[128],"To":[129],"end,":[131],"present":[133],"comprehensively":[137],"evaluate":[138],"performance.":[141],"With":[142],"comparison":[143],"traditional":[146],"way,":[147],"show":[149],"always":[152],"obtains":[153],"recovery":[155],"result":[156],"throughput":[159,166],"bound":[160],"around":[164],"25%":[165],"improvement":[167],"under":[168],"reconstruction":[170],"demand.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}