ArticlePloS one2020
The application of key feature extraction algorithm based on Gabor wavelet transformation in the diagnosis of lumbar intervertebral disc degenerative changes.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Analysis of characteristic features in ultrasound diagnosis of fetal limb body wall complex during 11-13World journal of clinical cases · 2023Article
- Article
- LncRNA LINC00324 is upregulated in intervertebral disk degeneration and upregulates FasL in nucleus pulposus cells.Molecular and cellular biochemistry · 2021Article
- The Clinical Diagnostic Value of Lumbar Intervertebral Disc Herniation Based on MRI Images.Journal of healthcare engineering · 2021Article
- Clinical and pathological considerations in lumbar herniated disc associated with inflammatory lesions.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
Corrections and comments
- Retraction · 2023-09-25Concerns/Issues about Peer Review · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveBased on the theoretical basis of Gabor wavelet transformation, the application effects of feature extraction algorithm in Magnetic Resonance Imaging (MRI) and the role of feature extraction algorithm in the diagnosis of lumbar vertebra degenerative diseases were explored.
methodThe structure of lumbar vertebra and degenerative changes were respectively introduced to clarify the onset mechanism and pathological changes of lumbar vertebra degenerative changes. Most importantly, the theoretical basis of Gabor wavelet transformation and the extraction effect of feature information in lumbar vertebra MRI images were introduced. The differentiation effects of feature information extraction algorithm on annulus fibrosus and nucleus pulposus were analyzed. In this study, the data of lumbar spine MRI was randomly selected from the Wenzhou Lumbar Spine Research Database as research objects. A total of 130 discs were successfully fitted, and 109 images were graded by a doctor after observation, which was compared with the results of the artificial diagnosis. Through the comparison with the results of observation and diagnosis by professional doctors, the accuracy of feature extraction algorithm based on Gabor wavelet transformation in the diagnosis of lumbar vertebra degenerative changes was analyzed.
results1. Compared with the results of the manual diagnosis, the accuracy of the classification method was 88.3%. In addition, the specificity (SPE), accuracy (ACC), and sensitivity (SEN) of the classification method were respectively 89.5%, 92.4%, and 87.6%. 2. The mutual information method and the KLT algorithm were utilized for vertebral body tracking. The maximum mutual information method was more effective in the case of fewer image sequences; however, with the increase of image frames, the accumulation of errors would make the tracking effects of images get worse. Based on the KLT algorithm, the enhanced vertebral boundary information was selected; the soft tissues showed in the obtained images were smooth, the boundary information of vertebral body was enhanced, and the results were more accurate.
conclusionThe feature extraction algorithm based on Gabor wavelet transformation could easily and quickly realize the localization of the lumbar intervertebral disc, and the accuracy of the results was ensured. In addition, from the aspect of vertebral body tracking, the tracking effects based on the KLT algorithm were better and faster than those based on the maximum mutual information method.
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