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Application of a semiautomatic classifier for modic and disk hernia changes in magnetic resonance

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DataCite Commons2022-06-07 更新2024-07-29 收录
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https://scielo.figshare.com/articles/dataset/Application_of_a_semiautomatic_classifier_for_modic_and_disk_hernia_changes_in_magnetic_resonance/20013523
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OBJECTIVE: Early detection of degenerative changes in lumbar intervertebral disc by magnetic resonance imaging in a semiautomatic classifier for prevention of degenerative disease. METHOD: MRIs were selected with a diagnosis of degenerative disc disease or back pain from January to May 2014, with a sample of 23 patients and a total of 170 disks evaluated by sagittal T2 MRI image, first evaluated by a specialist physician in training and them were introduced into the software, being the results compared. RESULTS: One hundred and fifteen discs were evaluated by a programmed semiautomatic classifier to identify MODIC changes and hernia, which produced results "normal or MODIC" and "normal or abnormal", respectively. With a total of 230 readings, of which 141 were correct, 84 were reading errors and 10 readings were undiagnosed, the semiautomatic classifier is a useful tool for early diagnosis or established disease and is easy to apply because of the speed and ease of use; however, at this early stage of development, software is inferior to clinical observations and the results were from around 65% to 60% certainty for MODIC rating and 61% to 58% for disc herniation, compared with clinical evaluations. CONCLUSION: The comparative results between the two doctors were 94 consistent results and only 21 errors, which represents 81% certainty.
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SciELO journals
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2022-06-07
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