biostudies-literatureUnknown14(12)Teng Z<h4>Background and objective</h4>Medical image segmentation is a vital aspect of medical image processing, allowing healthcare professionals to conduct precise and comprehensive lesion analyses. Traditional segmentation methods are often labor intensive and influenced by the subjectivity of individual physicians. The advent of artificial intelligence (AI) has transformed this field by reducing the workload of physicians, and improving the accuracy and efficiency of disease diagnosis. However, conventional AI techniques are not without challenges. Issues such as inexplicability, uncontrollable decision-making processes, and unpredictability can lead to confusion and uncertainty in clinical decision-making. This review explores the evolution of AI in medical image segmentation, focusing on tQuantitative imaging in medicine and surgery9620-9652https://www.ebi.ac.uk/biostudies/studies/S-EPMC11651983biostudies-literatureA literature review of artificial intelligence (AI) for medical image segmentation: from AI and explainable AI to trustworthy AI.PMC11651983Peng THuang JXiang DShi FCai JZhu WChen XTeng ZLi LZhou HXin ZfalseA literature review of artificial intelligence (AI) for medical image segmentation: from AI and explainable AI to trustworthy AI.<h4>Background and objective</h4>Medical image segmentation is a vital aspect of medical image processing, allowing healthcare professionals to conduct precise and comprehensive lesion analyses. Traditional segmentation methods are often labor intensive and influenced by the subjectivity of individual physicians. The advent of artificial intelligence (AI) has transformed this field by reducing the workload of physicians, and improving the accuracy and efficiency of disease diagnosis. However, conventional AI techniques are not without challenges. Issues such as inexplicability, uncontrollable decision-making processes, and unpredictability can lead to confusion and uncertainty in clinical decision-making. This review explores the evolution of AI in medical image segmentation, focusing on t2024-01-01T00:00:00Z2024 Dec2025-04-26T17:06:30.494Z2025-04-06T15:23:21.901ZS-EPMC116519833969866410.21037/qims-24-723