Heart disease is a significant global health problem, with increasing mortality and morbidity rates. Precise segmentation and classification of cardiac structures from 3D CT image reconstructions are critical for successful diagnosis, treatment planning, and patient management. This review discusses different approaches employed for heart disease segmentation and classification, particularly 3D CT image reconstruction. It gives an overview of ongoing developments, identifies major issues, and presents directions for future research. By bringing together current methods and new trends, this paper strives to improve diagnosis and treatment of heart disease, thereby aiming to lead to improvements in global public health.