Quantitative Computed Tomography (QCT) as a Radiology Reporting Tool by Using Optical Character Recognition (OCR) and Macro Program
Identifieur interne : 000247 ( Main/Exploration ); précédent : 000246; suivant : 000248Quantitative Computed Tomography (QCT) as a Radiology Reporting Tool by Using Optical Character Recognition (OCR) and Macro Program
Auteurs : Young Han Lee [Corée du Sud] ; Ho-Taek Song [Corée du Sud] ; Jin-Suck Suh [Corée du Sud]Source :
- Journal of Digital Imaging [ 0897-1889 ] ; 2012.
English descriptors
- KwdEn :
- MESH :
- methods : Tomography, X-Ray Computed.
- radiography : Bone Diseases, Metabolic, Femur Neck, Lumbar Vertebrae, Osteoporosis.
- Humans, Pattern Recognition, Automated, Radiology Information Systems, Software.
Abstract
The objectives are (1) to introduce a new concept of making a quantitative computed tomography (QCT) reporting system by using optical character recognition (OCR) and macro program and (2) to illustrate the practical usages of the QCT reporting system in radiology reading environment. This reporting system was created as a development tool by using an open-source OCR software and an open-source macro program. The main module was designed for OCR to report QCT images in radiology reading process. The principal processes are as follows: (1) to save a QCT report as a graphic file, (2) to recognize the characters from an image as a text, (3) to extract the
Url:
DOI: 10.1007/s10278-012-9464-8
PubMed: 22399206
PubMed Central: 3491163
Affiliations:
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Le document en format XML
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type="city">Séoul</settlement></placeName></affiliation></author><author><name sortKey="Song, Ho Taek" sort="Song, Ho Taek" uniqKey="Song H" first="Ho-Taek" last="Song">Ho-Taek Song</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752 Republic of Korea</nlm:aff><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul</wicri:regionArea><placeName><settlement type="city">Séoul</settlement></placeName></affiliation></author><author><name sortKey="Suh, Jin Suck" sort="Suh, Jin Suck" uniqKey="Suh J" first="Jin-Suck" last="Suh">Jin-Suck Suh</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752 Republic of Korea</nlm:aff><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul</wicri:regionArea><placeName><settlement type="city">Séoul</settlement></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22399206</idno><idno type="pmc">3491163</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3491163</idno><idno type="RBID">PMC:3491163</idno><idno 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Character Recognition (OCR) and Macro Program</title><author><name sortKey="Lee, Young Han" sort="Lee, Young Han" uniqKey="Lee Y" first="Young Han" last="Lee">Young Han Lee</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752 Republic of Korea</nlm:aff><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul</wicri:regionArea><placeName><settlement type="city">Séoul</settlement></placeName></affiliation></author><author><name sortKey="Song, Ho Taek" sort="Song, Ho Taek" uniqKey="Song H" first="Ho-Taek" last="Song">Ho-Taek Song</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752 Republic of Korea</nlm:aff><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul</wicri:regionArea><placeName><settlement type="city">Séoul</settlement></placeName></affiliation></author><author><name sortKey="Suh, Jin Suck" sort="Suh, Jin Suck" uniqKey="Suh J" first="Jin-Suck" last="Suh">Jin-Suck Suh</name><affiliation wicri:level="3"><nlm:aff id="Aff1">Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752 Republic of Korea</nlm:aff><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>Department of Radiology, Research Institute of Radiological Science, Medical Convergence Research Institute, and Severance Biomedical Science Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul</wicri:regionArea><placeName><settlement type="city">Séoul</settlement></placeName></affiliation></author></analytic><series><title level="j">Journal of Digital Imaging</title><idno type="ISSN">0897-1889</idno><idno type="eISSN">1618-727X</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Bone Diseases, Metabolic (radiography)</term><term>Femur Neck (radiography)</term><term>Humans</term><term>Lumbar Vertebrae (radiography)</term><term>Osteoporosis (radiography)</term><term>Pattern Recognition, Automated</term><term>Radiology Information Systems</term><term>Software</term><term>Tomography, X-Ray Computed (methods)</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Tomography, X-Ray Computed</term></keywords><keywords scheme="MESH" qualifier="radiography" xml:lang="en"><term>Bone Diseases, Metabolic</term><term>Femur Neck</term><term>Lumbar Vertebrae</term><term>Osteoporosis</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Humans</term><term>Pattern Recognition, Automated</term><term>Radiology Information Systems</term><term>Software</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>The objectives are (1) to introduce a new concept of making a quantitative computed tomography (QCT) reporting system by using optical character recognition (OCR) and macro program and (2) to illustrate the practical usages of the QCT reporting system in radiology reading environment. This reporting system was created as a development tool by using an open-source OCR software and an open-source macro program. The main module was designed for OCR to report QCT images in radiology reading process. The principal processes are as follows: (1) to save a QCT report as a graphic file, (2) to recognize the characters from an image as a text, (3) to extract the <italic>T</italic> scores from the text, (4) to perform error correction, (5) to reformat the values into QCT radiology reporting template, and (6) to paste the reports into the electronic medical record (EMR) or picture archiving and communicating system (PACS). The accuracy test of OCR was performed on randomly selected QCTs. QCT as a radiology reporting tool successfully acted as OCR of QCT. The diagnosis of normal, osteopenia, or osteoporosis is also determined. Error correction of OCR is done with AutoHotkey-coded module. The results of <italic>T</italic> scores of femoral neck and lumbar vertebrae had an accuracy of 100 and 95.4 %, respectively. A convenient QCT reporting system could be established by utilizing open-source OCR software and open-source macro program. This method can be easily adapted for other QCT applications and PACS/EMR.</p></div></front></TEI><affiliations><list><country><li>Corée du Sud</li></country><settlement><li>Séoul</li></settlement></list><tree><country name="Corée du Sud"><noRegion><name sortKey="Lee, Young Han" sort="Lee, Young Han" uniqKey="Lee Y" first="Young Han" last="Lee">Young Han Lee</name></noRegion><name sortKey="Song, Ho Taek" sort="Song, Ho Taek" uniqKey="Song H" first="Ho-Taek" last="Song">Ho-Taek Song</name><name sortKey="Suh, Jin Suck" sort="Suh, Jin Suck" uniqKey="Suh J" first="Jin-Suck" last="Suh">Jin-Suck Suh</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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