Digital image processing. I. Evaluation of gray level correction methods in vitro.
Identifieur interne : 003870 ( PubMed/Checkpoint ); précédent : 003869; suivant : 003871Digital image processing. I. Evaluation of gray level correction methods in vitro.
Auteurs : I. Fourmousis [Suisse] ; U. Br Gger ; W. Bürgin ; M. Tonetti ; N P LangSource :
- Clinical oral implants research [ 0905-7161 ] ; 1994.
Descripteurs français
- KwdFr :
- Absorptiométrie photonique (), Analyse de variance, Animaux, Artéfacts, Implants dentaires, Mandibule (imagerie diagnostique), Mâchoire édentée (imagerie diagnostique), Radiographie dentaire (), Reproductibilité des résultats, Sensibilité et spécificité, Suidae, Technique de soustraction, Traitement d'image par ordinateur.
- MESH :
English descriptors
- KwdEn :
- Absorptiometry, Photon (methods), Analysis of Variance, Animals, Artifacts, Dental Implants, Image Processing, Computer-Assisted, Jaw, Edentulous (diagnostic imaging), Mandible (diagnostic imaging), Radiography, Dental (methods), Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique, Swine.
- MESH :
- chemical : Dental Implants.
- diagnostic imaging : Jaw, Edentulous, Mandible.
- methods : Absorptiometry, Photon, Radiography, Dental.
- Analysis of Variance, Animals, Artifacts, Image Processing, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique, Swine.
Abstract
The aims of this study were a) to assess in an in vitro model the amount of density changes measured in digitally subtracted images due to electronic noise and image alignment error, and b) to test the accuracy of different gray level correction procedures in the reduction of densitometric image mismatches. A section of a pig mandible in which a hollow cylinder ITI Bonefit implant had been placed was used to obtain pairs of standardized radiographs. Series of radiographs were obtained with different exposure times (0.34, 0.39, 0.44, 0.51, 0.58 s). The radiographs were captured through a video camera, digitized and stored in a personal computer. The same radiographic image was recorded and subtracted from itself 10 times to study the error of the method due to electronic transformations of the images and image alignment. The noise due to the analog-to-digital transformation of the radiographic images was calculated to be +/- 2 gray levels i.e., 2% of the scale of gray levels. This kind of error was reduced up to 40% by capturing the images more than once and averaging the values per pixel. The manual superimposition of the images to be subtracted caused an increase of the error to +/- 3 gray levels (2.7%). Seven methods of gray level correction based either on a linear least squares approximation or on the cumulative density function (CDF) were tested. The group based on the CDF algorithm gave significantly better results than any other method. Pixels yielding differences smaller or equal to +/- 7 gray levels (5.5% of the scale of gray levels) should be excluded from further calculations in order to eliminate (false-positive) errors due to the normalizing algorithms. Furthermore, the CDF method on an arbitrarily chosen area of the image or on the wedge seems to give to subtraction images the ability of revealing real subtle changes in tissue density (fewer false-negative errors). The use of reference structures did not futher improve the ability of the normalization methods to correct gray level mismatches between radiographic pairs.
PubMed: 8038343
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Bürgin</name></author><author><name sortKey="Tonetti, M" sort="Tonetti, M" uniqKey="Tonetti M" first="M" last="Tonetti">M. Tonetti</name></author><author><name sortKey="Lang, N P" sort="Lang, N P" uniqKey="Lang N" first="N P" last="Lang">N P Lang</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="1994">1994</date><idno type="RBID">pubmed:8038343</idno><idno type="pmid">8038343</idno><idno type="wicri:Area/PubMed/Corpus">004464</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">004464</idno><idno type="wicri:Area/PubMed/Curation">004464</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">004464</idno><idno type="wicri:Area/PubMed/Checkpoint">004464</idno><idno type="wicri:explorRef" wicri:stream="Checkpoint" wicri:step="PubMed">004464</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Digital image processing. I. Evaluation of gray level correction methods in vitro.</title><author><name sortKey="Fourmousis, I" sort="Fourmousis, I" uniqKey="Fourmousis I" first="I" last="Fourmousis">I. Fourmousis</name><affiliation wicri:level="1"><nlm:affiliation>Department of Periodontology and Fixed Prosthodontics, University of Berne School of Dental Medicine, Switzerland.</nlm:affiliation><country xml:lang="fr">Suisse</country><wicri:regionArea>Department of Periodontology and Fixed Prosthodontics, University of Berne School of Dental Medicine</wicri:regionArea><wicri:noRegion>University of Berne School of Dental Medicine</wicri:noRegion></affiliation></author><author><name sortKey="Br Gger, U" sort="Br Gger, U" uniqKey="Br Gger U" first="U" last="Br Gger">U. Br Gger</name></author><author><name sortKey="Burgin, W" sort="Burgin, W" uniqKey="Burgin W" first="W" last="Bürgin">W. Bürgin</name></author><author><name sortKey="Tonetti, M" sort="Tonetti, M" uniqKey="Tonetti M" first="M" last="Tonetti">M. Tonetti</name></author><author><name sortKey="Lang, N P" sort="Lang, N P" uniqKey="Lang N" first="N P" last="Lang">N P Lang</name></author></analytic><series><title level="j">Clinical oral implants research</title><idno type="ISSN">0905-7161</idno><imprint><date when="1994" type="published">1994</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Absorptiometry, Photon (methods)</term><term>Analysis of Variance</term><term>Animals</term><term>Artifacts</term><term>Dental Implants</term><term>Image Processing, Computer-Assisted</term><term>Jaw, Edentulous (diagnostic imaging)</term><term>Mandible (diagnostic imaging)</term><term>Radiography, Dental (methods)</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Subtraction Technique</term><term>Swine</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Absorptiométrie photonique ()</term><term>Analyse de variance</term><term>Animaux</term><term>Artéfacts</term><term>Implants dentaires</term><term>Mandibule (imagerie diagnostique)</term><term>Mâchoire édentée (imagerie diagnostique)</term><term>Radiographie dentaire ()</term><term>Reproductibilité des résultats</term><term>Sensibilité et spécificité</term><term>Suidae</term><term>Technique de soustraction</term><term>Traitement d'image par ordinateur</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>Dental Implants</term></keywords><keywords scheme="MESH" qualifier="diagnostic imaging" xml:lang="en"><term>Jaw, Edentulous</term><term>Mandible</term></keywords><keywords scheme="MESH" qualifier="imagerie diagnostique" xml:lang="fr"><term>Mandibule</term><term>Mâchoire édentée</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Absorptiometry, Photon</term><term>Radiography, Dental</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Analysis of Variance</term><term>Animals</term><term>Artifacts</term><term>Image Processing, Computer-Assisted</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Subtraction Technique</term><term>Swine</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Absorptiométrie photonique</term><term>Analyse de variance</term><term>Animaux</term><term>Artéfacts</term><term>Implants dentaires</term><term>Radiographie dentaire</term><term>Reproductibilité des résultats</term><term>Sensibilité et spécificité</term><term>Suidae</term><term>Technique de soustraction</term><term>Traitement d'image par ordinateur</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The aims of this study were a) to assess in an in vitro model the amount of density changes measured in digitally subtracted images due to electronic noise and image alignment error, and b) to test the accuracy of different gray level correction procedures in the reduction of densitometric image mismatches. A section of a pig mandible in which a hollow cylinder ITI Bonefit implant had been placed was used to obtain pairs of standardized radiographs. Series of radiographs were obtained with different exposure times (0.34, 0.39, 0.44, 0.51, 0.58 s). The radiographs were captured through a video camera, digitized and stored in a personal computer. The same radiographic image was recorded and subtracted from itself 10 times to study the error of the method due to electronic transformations of the images and image alignment. The noise due to the analog-to-digital transformation of the radiographic images was calculated to be +/- 2 gray levels i.e., 2% of the scale of gray levels. This kind of error was reduced up to 40% by capturing the images more than once and averaging the values per pixel. The manual superimposition of the images to be subtracted caused an increase of the error to +/- 3 gray levels (2.7%). Seven methods of gray level correction based either on a linear least squares approximation or on the cumulative density function (CDF) were tested. The group based on the CDF algorithm gave significantly better results than any other method. Pixels yielding differences smaller or equal to +/- 7 gray levels (5.5% of the scale of gray levels) should be excluded from further calculations in order to eliminate (false-positive) errors due to the normalizing algorithms. Furthermore, the CDF method on an arbitrarily chosen area of the image or on the wedge seems to give to subtraction images the ability of revealing real subtle changes in tissue density (fewer false-negative errors). The use of reference structures did not futher improve the ability of the normalization methods to correct gray level mismatches between radiographic pairs.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">8038343</PMID><DateCompleted><Year>1994</Year><Month>08</Month><Day>19</Day></DateCompleted><DateRevised><Year>2016</Year><Month>11</Month><Day>23</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0905-7161</ISSN><JournalIssue CitedMedium="Print"><Volume>5</Volume><Issue>1</Issue><PubDate><Year>1994</Year><Month>Mar</Month></PubDate></JournalIssue><Title>Clinical oral implants research</Title><ISOAbbreviation>Clin Oral Implants Res</ISOAbbreviation></Journal><ArticleTitle>Digital image processing. I. Evaluation of gray level correction methods in vitro.</ArticleTitle><Pagination><MedlinePgn>37-47</MedlinePgn></Pagination><Abstract><AbstractText>The aims of this study were a) to assess in an in vitro model the amount of density changes measured in digitally subtracted images due to electronic noise and image alignment error, and b) to test the accuracy of different gray level correction procedures in the reduction of densitometric image mismatches. A section of a pig mandible in which a hollow cylinder ITI Bonefit implant had been placed was used to obtain pairs of standardized radiographs. Series of radiographs were obtained with different exposure times (0.34, 0.39, 0.44, 0.51, 0.58 s). The radiographs were captured through a video camera, digitized and stored in a personal computer. The same radiographic image was recorded and subtracted from itself 10 times to study the error of the method due to electronic transformations of the images and image alignment. The noise due to the analog-to-digital transformation of the radiographic images was calculated to be +/- 2 gray levels i.e., 2% of the scale of gray levels. This kind of error was reduced up to 40% by capturing the images more than once and averaging the values per pixel. The manual superimposition of the images to be subtracted caused an increase of the error to +/- 3 gray levels (2.7%). Seven methods of gray level correction based either on a linear least squares approximation or on the cumulative density function (CDF) were tested. The group based on the CDF algorithm gave significantly better results than any other method. Pixels yielding differences smaller or equal to +/- 7 gray levels (5.5% of the scale of gray levels) should be excluded from further calculations in order to eliminate (false-positive) errors due to the normalizing algorithms. Furthermore, the CDF method on an arbitrarily chosen area of the image or on the wedge seems to give to subtraction images the ability of revealing real subtle changes in tissue density (fewer false-negative errors). The use of reference structures did not futher improve the ability of the normalization methods to correct gray level mismatches between radiographic pairs.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Fourmousis</LastName><ForeName>I</ForeName><Initials>I</Initials><AffiliationInfo><Affiliation>Department of Periodontology and Fixed Prosthodontics, University of Berne School of Dental Medicine, Switzerland.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Brägger</LastName><ForeName>U</ForeName><Initials>U</Initials></Author><Author ValidYN="Y"><LastName>Bürgin</LastName><ForeName>W</ForeName><Initials>W</Initials></Author><Author ValidYN="Y"><LastName>Tonetti</LastName><ForeName>M</ForeName><Initials>M</Initials></Author><Author ValidYN="Y"><LastName>Lang</LastName><ForeName>N P</ForeName><Initials>NP</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>Denmark</Country><MedlineTA>Clin Oral Implants Res</MedlineTA><NlmUniqueID>9105713</NlmUniqueID><ISSNLinking>0905-7161</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D015921">Dental Implants</NameOfSubstance></Chemical></ChemicalList><CitationSubset>D</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D015502" MajorTopicYN="N">Absorptiometry, Photon</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000704" MajorTopicYN="N">Analysis of Variance</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016477" MajorTopicYN="N">Artifacts</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015921" MajorTopicYN="N">Dental Implants</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007091" MajorTopicYN="Y">Image Processing, Computer-Assisted</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007575" MajorTopicYN="N">Jaw, Edentulous</DescriptorName><QualifierName UI="Q000000981" MajorTopicYN="N">diagnostic imaging</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008334" MajorTopicYN="N">Mandible</DescriptorName><QualifierName UI="Q000000981" MajorTopicYN="Y">diagnostic imaging</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011861" MajorTopicYN="N">Radiography, Dental</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012680" MajorTopicYN="N">Sensitivity and Specificity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013382" MajorTopicYN="Y">Subtraction Technique</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013552" MajorTopicYN="N">Swine</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>1994</Year><Month>3</Month><Day>1</Day></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>1994</Year><Month>3</Month><Day>1</Day><Hour>0</Hour><Minute>1</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>1994</Year><Month>3</Month><Day>1</Day><Hour>0</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">8038343</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Suisse</li></country></list><tree><noCountry><name sortKey="Br Gger, U" sort="Br Gger, U" uniqKey="Br Gger U" first="U" last="Br Gger">U. Br Gger</name><name sortKey="Burgin, W" sort="Burgin, W" uniqKey="Burgin W" first="W" last="Bürgin">W. Bürgin</name><name sortKey="Lang, N P" sort="Lang, N P" uniqKey="Lang N" first="N P" last="Lang">N P Lang</name><name sortKey="Tonetti, M" sort="Tonetti, M" uniqKey="Tonetti M" first="M" last="Tonetti">M. Tonetti</name></noCountry><country name="Suisse"><noRegion><name sortKey="Fourmousis, I" sort="Fourmousis, I" uniqKey="Fourmousis I" first="I" last="Fourmousis">I. Fourmousis</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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