| Abstrakt: |
The liver cancer is the sixth most cause for mortality due to cancers. The survival rate of liver cancer is extremely low because of complexities in early diagnosis, hasty progression, and a shortage of targeted drugs. Liver cancer detection is challenging because of diversity in morphology, risk factors, micro-environmental discrepancies, and genetic susceptibilities. This paper presents a survey of computer-aided liver cancer detection using distinct machine and deep learning techniques. It focuses on the methodology, dataset, evaluation metrics, challenges and constraints of the various machine- and deep learning-based liver cancer detection approaches. It presents the future direction of liver cancer detection for further enhancement. |
