ABSTRACT
In recent years, deep learning algorithms have become the standard approach for analyzing fetal images obtained through ultrasound technology. This chapter surveys the most up-to-date works and case studies on foetal image analysis using machine learning and deep learning. Each article is analyzed and discussed from a methodology and application perspective. Papers are categorized into (i) traditional ultrasound analysis, (ii) artificial intelligence for foetal ultrasound image analysis, and (iii) deep learning for foetal ultrasound image analysis. The primary restrictions and unresolved problems are listed for each category. To make it easier to compare the various strategies, summary tables are provided. To integrate the research techniques into practical clinical practice, researchers working in the field must overcome hurdles of DL algorithms for foetal ultrasound picture analysis.
