A Review on Medical Image Segmentation Using Deep Learning

Medical image segmentation plays a crucial role in the healthcare industry by facilitating accurate illustration of anatomical structures and abnormalities from images. Deep learning has led to transformative improvements in the medical field in precision and efficiency. This paper comprehensively reviews deep learning techniques in medical image segmentation. The challenges in this domain including annotated data, anomaly detection, noise reduction, and privacy concerns are discussed. The paper outlines future directions emphasizing GAN, multi-modal integration, and adversarial robustness and provides a valuable resource for researchers by offering insights about the current trend and future directions of medical image segmentation.