Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models.

ABSTRACT: Spondylolisthesis refers to the slippage of one vertebral body over the adjacent one. It is a chronic condition that requires early detection to prevent unpleasant surgery. The paper presents an optimized deep learning model for detecting spondylolisthesis in X-ray radiographs. The dataset contains a total of 299 X-ray radiographs from which 156 images are showing the spine with spondylolisthesis and 143 images are of the normal spine. Image augmentation technique is used to increase the data samples. In this study, VGG16 and InceptionV3 models were used for the image classification task. The developed model is optimized by utilizing the TFLite model optimization technique. The experimental result shows that the VGG16 model has achieved a 98% accuracy rate, which is higher than InceptionV3

SUBMITTER: Saravagi D 

PROVIDER: S-EPMC9007141 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature