CT Image Features of the FBP Reconstruction Algorithm in the Evaluation of Fasting Blood Sugar Level of Diabetic Pulmonary Tuberculosis Patients and Early Diet Nursing
The study was aimed at exploring the application value of the CT image based on a filtered back projection (FBP) algorithm in the diagnosis of patients with diabetes complicated with tuberculosis and at analyzing the influence of dietary nursing on patients with diabetes complicated with tuberculosi...
Guardado en:
Autores principales: | Lili Hong, Liling Lin, Jingping Chen, Biyu Wu |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Hindawi Limited
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/27d59614499f4fbc8f7e8f02eed8ff34 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
por: Shih-Cheng Huang, et al.
Publicado: (2020) -
Author Correction: PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
por: Shih-Cheng Huang, et al.
Publicado: (2020) -
Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT
por: Edward H. Lee, et al.
Publicado: (2021) -
A Study on Weak Edge Detection of COVID-19’s CT Images Based on Histogram Equalization and Improved Canny Algorithm
por: Shou-Ming Hou, et al.
Publicado: (2021) -
Utilization of Nursing Defect Management Evaluation and Deep Learning in Nursing Process Reengineering Optimization
por: Yue Liu, et al.
Publicado: (2021)