Background: Over the last few years, there has been increasing interest in the use of artificial intelligence to assist with abnormality detection on medical images. Aim of this study was to investigate the performance of Artificial Intelligence on the detection of trauma in liver with High Resolution Multi slice Computed Tomography. Methods: this prospective study was done on 65 cases, who underwent automatic detection of liver trauma based on computer-aided detection systems, focuses on the artificial intelligence technology applied in liver multislice CT scans Using High Resolution Multi slice Computed Tomography ( 16/64/128 detector ) for liver examination for abnormality detected by artificial intelligence technology. Results: a mean age of 20 years with a standard deviation of 15 years. The diagnostic performance of artificial intelligence for detecting liver lesions was analyzed. The models demonstrated good agreement for detecting hepatic lesions. Conclusion: The proposed algorithms can accurately segment the liver and the regions affected by trauma. This pipeline demonstrates an accurate performance in estimating the percentage of liver parenchyma that is affected by trauma. Such a system can aid critical care medical personnel by providing a reproducible quantitative assessment of liver trauma as an alternative to the sometimes- subjective AAST grading system that is used currently