In this present era of technology, segmentation of image is a fundamental and significant component of computer vision and image processing applications. These applications include medical image analysis, compression of images, surveillance, security footage, and many others. Researchers have proposed and developed various models, theories, and algorithms in this advancing field of image segmentation. Due to the success of a wide range of computer vision applications, work whose goal was to use deep learning algorithms for the development and usability of image segmentation was completed not long ago. In this study, a detailed review of the literature on image segmentation is being written, which covers a vast and extensive amount of work done by researchers at the time of writing this review. This review investigates the similarity and differences between the proposed models by researchers in the past. Along with similarities, we have also discussed the strength and challenges of the model under the umbrella of deep learning algorithms. In the end, future work has been discussed along with keeping in view the past work of researchers.