{"id":"https://openalex.org/W4402979679","doi":"https://doi.org/10.1109/icme57554.2024.10687679","title":"Frequency-regularized Neural Representation Method for Sparse-view Tomographic Reconstruction","display_name":"Frequency-regularized Neural Representation Method for Sparse-view Tomographic Reconstruction","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402979679","doi":"https://doi.org/10.1109/icme57554.2024.10687679"},"language":"en","primary_location":{"id":"doi:10.1109/icme57554.2024.10687679","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10687679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","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/A5111346910","display_name":"Jingmou Xian","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingmou Xian","raw_affiliation_strings":["Science Guangdong University of Technology,School of Computer,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Science Guangdong University of Technology,School of Computer,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088444199","display_name":"Jian Zhu","orcid":"https://orcid.org/0000-0002-2551-2024"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhu","raw_affiliation_strings":["Science Guangdong University of Technology,School of Computer,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Science Guangdong University of Technology,School of Computer,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113409480","display_name":"Haolin Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haolin Liao","raw_affiliation_strings":["Science Guangdong University of Technology,School of Computer,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Science Guangdong University of Technology,School of Computer,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391306","display_name":"Si Li","orcid":"https://orcid.org/0000-0001-5590-7759"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Si Li","raw_affiliation_strings":["Science Guangdong University of Technology,School of Computer,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Science Guangdong University of Technology,School of Computer,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5111346910"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28839625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9904000163078308,"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"}},"topics":[{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9904000163078308,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9724000096321106,"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"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9639000296592712,"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":0.6305367350578308},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.5829594731330872},{"id":"https://openalex.org/keywords/tomographic-reconstruction","display_name":"Tomographic reconstruction","score":0.5732598900794983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5637764930725098},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.550611138343811},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.533519446849823},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44664108753204346},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4147326350212097}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6305367350578308},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5829594731330872},{"id":"https://openalex.org/C97742081","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Tomographic reconstruction","level":3,"score":0.5732598900794983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5637764930725098},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.550611138343811},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.533519446849823},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44664108753204346},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4147326350212097},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme57554.2024.10687679","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icme57554.2024.10687679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1964749215","https://openalex.org/W2982317495","https://openalex.org/W2088308468","https://openalex.org/W170151271","https://openalex.org/W2017732498","https://openalex.org/W2137532034","https://openalex.org/W2947117330","https://openalex.org/W2295596929","https://openalex.org/W1574221054","https://openalex.org/W2004988775"],"abstract_inverted_index":{"Sparse-view":[0],"tomographic":[1,24,82],"reconstruction":[2,22],"is":[3],"a":[4],"pivotal":[5],"direction":[6],"for":[7,79],"reducing":[8],"radiation":[9],"dose":[10],"and":[11,61,107,116,119],"augmenting":[12],"clinical":[13],"applicability.":[14],"While":[15],"many":[16],"research":[17],"works":[18],"have":[19],"proposed":[20],"the":[21,44,64,72,93,98],"of":[23],"images":[25],"from":[26],"sparse":[27,45],"2D":[28],"projections,":[29],"existing":[30],"models":[31],"tend":[32],"to":[33,55],"excessively":[34],"focus":[35],"on":[36,114],"high-frequency":[37,51,106],"information":[38,52],"while":[39],"overlooking":[40],"low-frequency":[41,108],"components":[42],"within":[43],"input":[46],"images.":[47],"This":[48,102],"bias":[49],"towards":[50],"often":[53],"leads":[54],"overfitting,":[56],"particularly":[57],"intense":[58],"at":[59],"edges":[60],"boundaries":[62],"in":[63,97],"reconstructed":[65],"slices.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70],"introduce":[71],"Frequency":[73],"Regularized":[74],"Neural":[75],"Attenuation/Activity":[76],"Field":[77],"(Freq-NAF)":[78],"self-supervised":[80],"sparse-view":[81],"reconstruction.":[83],"Freq-NAF":[84],"mitigates":[85],"overfitting":[86],"by":[87],"incorporating":[88],"frequency":[89,95],"regularization,":[90],"directly":[91],"controlling":[92],"visible":[94],"bands":[96],"neural":[99],"network":[100],"input.":[101],"approach":[103],"effectively":[104],"balances":[105],"information.":[109],"We":[110],"conducted":[111],"numerical":[112],"experiments":[113],"CBCT":[115],"SPECT":[117],"datasets,":[118],"our":[120],"method":[121],"demonstrates":[122],"state-of-the-art":[123],"accuracy.":[124]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
