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Improving Image Correlation and Differentiation of 3D Endoluminal Lesions in the Air Spaces Using a Novel Target Gray Level Mapping Technique: A Preliminary Study of Its Application to Computed Tomographic Colonography and Comparison with Traditional Surface Rendering Method.

Lih-Shyang ChenTa-Wen HsuShao-Jer ChenShu-Han ChangChih-Wen LinYu-Ruei ChenChin-Chiang HsiehShu-Chen HanKu-Yaw ChangChun-Ju Hou
Published in: Journal of medical and biological engineering (2020)
Compared with only the spatial shape information in traditional SR of CTC images, the 3D shapes and gray level information of endoluminal lesions can be provided by TGM simultaneously. 3D to 2D image correlations are also increased and facilitated at the same time. TGM is less affected by adjacent colon surfaces than GM. TGM serves as a better way to improve the image correlation and differentiation of endoluminal lesions.
Keyphrases
  • deep learning
  • health information
  • high resolution
  • convolutional neural network
  • optical coherence tomography
  • machine learning
  • escherichia coli
  • cystic fibrosis
  • biofilm formation
  • candida albicans