Automatic Segmentation of liver Tumor using Deep Learning

Authors

  • Mrinalini kakroo Student, Department of Computer Science & IT, University of Jammu, Jammu, India
  • Vibhakar mansotra Professor, Department of Computer Science & IT, University of Jammu, Jammu, India

DOI:

https://doi.org/10.5281/zenodo.8276825

Keywords:

Deep Learning, Segmentation, Tumors

Abstract

When it comes to medical imaging data like CT or MRI images, automatic segmentation of liver tumors is the process of precisely locating and isolating tumor spots without the need for human involvement. Liver tumor segmentation is crucial for accurate diagnosis and therapeutic planning of liver cancer. The purpose of this work is to provide a comprehensive summary of the state-of-the-art approaches to automatically segmenting liver cancers from medical imaging data. Here, we'll go through some of the more general and specialized approaches now in use in this field. By allowing for more precise tumor delineation, this technology may help doctors improve patient outcomes via prompt, individualized treatment. With increased research and collaboration between the medical and AI fields, deep learning-based liver tumor segmentation has the potential to become a vital weapon in the fight against liver cancer.

Published

23-08-2023

How to Cite

Mrinalini kakroo, & Vibhakar mansotra. (2023). Automatic Segmentation of liver Tumor using Deep Learning. Journal of Scientific Research and Technology, 1(5), 100–113. https://doi.org/10.5281/zenodo.8276825