Elucidating the novel framework of liver tumour segmentation and classification using improved Optimization-assisted EfficientNet B7 learning model

This publication has 33 references indexed in Scilit:

• A study on the optimal condition of ground truth area for liver tumor detection in ultrasound images using deep learning
  Journal of Medical Ultrasonics, 2023
• Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field
  Computers in Biology and Medicine, 2022
• A diagnosis system by U-net and deep neural network enabled with optimal feature selection for liver tumor detection using CT images
  Multimedia Tools and Applications, 2022
• Automatic liver and tumor segmentation based on deep learning and globally optimized refinement
  Applied Mathematics-A Journal of Chinese Universities, 2021
• RETRACTED ARTICLE: Automatic segmentation and classification of liver tumor from CT image using feature difference and SVM based classifier-soft computing technique
  Soft Computing, 2020
• OPBS-SSHC: outline preservation based segmentation and search based hybrid classification techniques for liver tumor detection
  Multimedia Tools and Applications, 2020
• Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies
  Medical & Biological Engineering & Computing, 2018
• Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans
  International Journal of Computer Assisted Radiology and Surgery, 2016
• Accelerated liver tumor segmentation in four-phase computed tomography images
  Journal of Real-Time Image Processing, 2016
• Liver tumors segmentation from CTA images using voxels classification and affinity constraint propagation
  International Journal of Computer Assisted Radiology and Surgery, 2010