Application of Medical Imaging Based on Deep Learning in the Treatment of Lumbar Degenerative Diseases and Osteoporosis with Bone Cement Screws.
Comput Math Methods Med
; 2021: 2638495, 2021.
Article
en En
| MEDLINE
| ID: mdl-34671416
ABSTRACT
OBJECTIVE:
To explore the application value of magnetic resonance spectroscopy (MRS) and GSI-energy spectrum electronic computed tomography (CT) medical imaging based on the deep convolutional neural network (CNN) in the treatment of lumbar degenerative disease and osteoporosis.METHODS:
There were 56 cases of suspected lumbar degenerative disease and osteoporosis. A group of 56 subjects were examined using 1.5 TMR spectrum (MRS) and dual-energy X-ray absorptiometry (DXA) to collect the lumbar L3 vertebral body fat ratio (FF) and L1~4 vertebral bone mineral density (BMD) value. We divided the subjects into 2 groups with T value -2.5 as the critical point. Set T value > -2.5 as the negative group and T value ≤ -2.5 as the positive group. Pearson's method is used for FF-MRS and BMD correlation analyses. A group of all patients underwent GSI-energy spectrum CT scan, and X-ray bone mineral density (DXA) test results (bone density per unit area) were used as the gold standard to analyze the diagnosis of osteoporosis by the GSI-energy spectrum CT scan method value.RESULTS:
The differences in FF and BMD between the negative group and the positive group were statistically significant (P < 0.01), and there was a highly negative correlation between the average value of FF and BMD. 30 cases were diagnosed as osteoporosis by DXA. The accuracy of GSI-energy spectrum CT medical imaging in diagnosing osteoporosis is 89.30%. The GSI-energy spectrum CT diagnosis of osteoporosis and DXA examination results have good consistency.CONCLUSION:
Based on the deep convolutional neural network (CNN) MRS technology, GSI-energy spectrum CT medical imaging is used in the clinical diagnosis and treatment of lumbar degenerative lesions and osteoporosis. It has a good advantage in assessing bone quality and has good consistency with DXA examination and has better application value high.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Osteoporosis
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Enfermedades Óseas
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Interpretación de Imagen Asistida por Computador
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Aprendizaje Profundo
Límite:
Adult
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Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Comput Math Methods Med
Asunto de la revista:
INFORMATICA MEDICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
China