{"id":"https://openalex.org/W2996547442","doi":"https://doi.org/10.1109/tip.2019.2957941","title":"Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield Microscopy","display_name":"Parameter-Free Gaussian PSF Model for Extended Depth of Field in Brightfield Microscopy","publication_year":2019,"publication_date":"2019-12-12","ids":{"openalex":"https://openalex.org/W2996547442","doi":"https://doi.org/10.1109/tip.2019.2957941","mag":"2996547442","pmid":"https://pubmed.ncbi.nlm.nih.gov/31831426"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2957941","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2957941","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5083006731","display_name":"Xu Zhou","orcid":"https://orcid.org/0000-0001-6152-5941"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Zhou","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023830568","display_name":"Rafael Molina","orcid":"https://orcid.org/0000-0003-4694-8588"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Rafael Molina","raw_affiliation_strings":["Departamento de Ciencias de la Computaci\u00f3n e Inteligencia Artificial, E. T. S. I. Inform\u00e1tica y Telecomunicaci\u00f3n, Universidad de Granada, Granada, Spain"],"affiliations":[{"raw_affiliation_string":"Departamento de Ciencias de la Computaci\u00f3n e Inteligencia Artificial, E. T. S. I. Inform\u00e1tica y Telecomunicaci\u00f3n, Universidad de Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062841020","display_name":"Yi Ma","orcid":"https://orcid.org/0000-0001-5485-419X"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Ma","raw_affiliation_strings":["Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046543349","display_name":"Tianfu Wang","orcid":"https://orcid.org/0000-0002-1248-1214"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianfu Wang","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065374358","display_name":"Dong Ni","orcid":"https://orcid.org/0000-0002-9146-6003"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Ni","raw_affiliation_strings":["School of Biomedical Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Biomedical Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5083006731"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":0.905,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.79723424,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"29","issue":null,"first_page":"3227","last_page":"3238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11897","display_name":"Digital Holography and Microscopy","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9855999946594238,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7451342344284058},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6856950521469116},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6718701124191284},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.6323109865188599},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6107688546180725},{"id":"https://openalex.org/keywords/depth-of-field","display_name":"Depth of field","score":0.5888145565986633},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5378811359405518},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5093036890029907},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.44796329736709595},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.42905041575431824},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38928598165512085},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3665718138217926},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.2887910008430481},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2536136209964752},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15100371837615967}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7451342344284058},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6856950521469116},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6718701124191284},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.6323109865188599},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6107688546180725},{"id":"https://openalex.org/C183072630","wikidata":"https://www.wikidata.org/wiki/Q215932","display_name":"Depth of field","level":2,"score":0.5888145565986633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5378811359405518},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5093036890029907},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.44796329736709595},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.42905041575431824},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38928598165512085},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3665718138217926},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2887910008430481},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2536136209964752},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15100371837615967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2019.2957941","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2957941","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:31831426","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31831426","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G122031786","display_name":null,"funder_award_id":"DPI2016-77869-C2-2-R","funder_id":"https://openalex.org/F4320321837","funder_display_name":"Ministerio de Econom\u00eda y Competitividad"},{"id":"https://openalex.org/G1339716967","display_name":null,"funder_award_id":"KQJSCX20180328095606003","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G444845467","display_name":null,"funder_award_id":"61571304","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5622395626","display_name":null,"funder_award_id":"KQTD2016053112051497","funder_id":"https://openalex.org/F4320335790","funder_display_name":"Shenzhen Peacock Plan"},{"id":"https://openalex.org/G7202197703","display_name":null,"funder_award_id":"B2018031","funder_id":"https://openalex.org/F4320322161","funder_display_name":"Guangdong Medical Research Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321837","display_name":"Ministerio de Econom\u00eda y Competitividad","ror":"https://ror.org/034900433"},{"id":"https://openalex.org/F4320322161","display_name":"Guangdong Medical Research Foundation","ror":null},{"id":"https://openalex.org/F4320335790","display_name":"Shenzhen Peacock Plan","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W136713118","https://openalex.org/W1638789865","https://openalex.org/W1916731006","https://openalex.org/W1965475047","https://openalex.org/W1983078517","https://openalex.org/W1987075379","https://openalex.org/W1994710939","https://openalex.org/W1996987333","https://openalex.org/W1999034606","https://openalex.org/W2039465985","https://openalex.org/W2046672499","https://openalex.org/W2051035598","https://openalex.org/W2051434435","https://openalex.org/W2064000601","https://openalex.org/W2071367684","https://openalex.org/W2079188893","https://openalex.org/W2081754635","https://openalex.org/W2099712288","https://openalex.org/W2103559027","https://openalex.org/W2116702374","https://openalex.org/W2116955664","https://openalex.org/W2119599674","https://openalex.org/W2127651471","https://openalex.org/W2128254445","https://openalex.org/W2142224114","https://openalex.org/W2143789285","https://openalex.org/W2154571593","https://openalex.org/W2166774562","https://openalex.org/W2168308200","https://openalex.org/W2276154416","https://openalex.org/W2293441561","https://openalex.org/W2507550467","https://openalex.org/W2559870345","https://openalex.org/W2622677389","https://openalex.org/W2766445487","https://openalex.org/W2777967210","https://openalex.org/W2790267366","https://openalex.org/W2914139557","https://openalex.org/W3098378321","https://openalex.org/W4247043502","https://openalex.org/W4293775970","https://openalex.org/W6605552958","https://openalex.org/W6747489832"],"related_works":["https://openalex.org/W79315950","https://openalex.org/W2751326998","https://openalex.org/W2357322570","https://openalex.org/W90581812","https://openalex.org/W2997591215","https://openalex.org/W2227541280","https://openalex.org/W2803858372","https://openalex.org/W4287992335","https://openalex.org/W4285261393","https://openalex.org/W2131818386"],"abstract_inverted_index":{"Due":[0],"to":[1,20,26,120,133],"their":[2],"limited":[3],"depth":[4,85,136],"of":[5,30],"field,":[6],"conventional":[7],"brightfield":[8],"microscopes":[9],"cannot":[10,51],"image":[11,24,47,80,91,97,123],"thick":[12],"specimens":[13],"entirely":[14],"in":[15,55,76,90],"focus.":[16],"A":[17],"common":[18],"way":[19],"obtain":[21],"an":[22,112,125],"all-in-focus":[23,79],"is":[25,61,118,131],"acquire":[27],"a":[28,40,71,107,109],"z-stack":[29,104],"images":[31],"by":[32],"optically":[33],"sectioning":[34],"the":[35,53,58,78,84,96,103,122,135,150,154],"specimen":[36],"and":[37,87,124,138,145,160],"then":[38],"apply":[39],"multi-focus":[41],"fusion":[42,49,158],"method.":[43],"Unfortunately,":[44],"for":[45],"undersampled":[46],"stacks,":[48],"methods":[50],"remove":[52],"blur":[54],"regions":[56],"where":[57],"in-focus":[59],"position":[60],"between":[62],"two":[63],"optical":[64],"sections.":[65],"In":[66,106],"this":[67],"work,":[68],"we":[69],"propose":[70],"parameter-free":[72],"Gaussian":[73],"PSF":[74],"model":[75],"which":[77],"together":[81],"with":[82],"both":[83],"map":[86,137],"sampling":[88,139],"distances":[89,140],"plane":[92],"are":[93],"estimated":[94],"from":[95],"sequence":[98],"automatically,":[99],"without":[100],"knowledge":[101],"on":[102,143],"acquisition.":[105],"maximum":[108],"posteriori":[110],"framework,":[111],"iteratively":[113],"reweighted":[114],"least":[115],"squares":[116],"method":[117,130,152],"used":[119],"estimate":[121,134],"adaptive":[126],"scaled":[127],"gradient":[128],"descent":[129],"utilized":[132],"efficiently.":[141],"Experiments":[142],"synthetic":[144],"real":[146],"data":[147],"demonstrate":[148],"that":[149],"proposed":[151],"outperforms":[153],"current":[155],"state-of-the-art,":[156],"mitigating":[157],"artifacts":[159],"recovering":[161],"sharper":[162],"edges.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
