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Automatic liver and tumour segmentation from CT images using Deep learning algorithm

  • Published:2022-03 Issue: Volume:6 Page:100087
  • ISSN:2666-7207
  • Container-title:Results in Control and Optimization
  • language:en
  • Short-container-title:Results in Control and Optimization

Author:

Manjunath R.V.,Kwadiki Karibasappa

Publisher

Elsevier BV

Reference24 articles.

1. World health organization. http://www.who.int/mediacentre/factsheets/fs297/en/.

2. 3D deeply supervised network for automated segmentation of volumetric medical images;Dou;Med Image Anal,2017

3. Automatic liver segmentation in abdomen CT images using SLIC and AdaBoost algorithms;Barstugan. R. Ceylan,2018

4. Diagnosis of liver tumor from CT images using first order statistical;Ali;Int J Eng Trends Technol (IJETT),2015

5. Computer-aided diagnosis of liver tumors on computed tomography images;Chang;Comput Methods Programs Biomed,2017

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1. PSO-PSP-Net + InceptionV3: An optimized hyper-parameter tuned Computer-Aided Diagnostic model for liver tumor detection using CT scan slices;Biomedical Signal Processing and Control;2024-09

2. Grey Wolf optimized SwinUNet based transformer framework for liver segmentation from CT images;Computers and Electrical Engineering;2024-07

3. Transformer Skip‐Fusion Based SwinUNet for Liver Segmentation From CT Images;International Journal of Imaging Systems and Technology;2024-06-24

4. Advancements in Automated Tumor Detection Screening: A Comprehensive Review and Comparative Analysis;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

5. A Comprehensive Liver Tumor Detection and Stages Classification Using Deep Learning and Image Processing Techniques;2024 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES);2024-05-03
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