U-Net and its variants for medical image segmentation: theory and applications

U-net is an image segmentation technique developed primarily for medical image analysis that can precisely segment images using a scarce amount of training data. These traits provide U-net with a very high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for segmentation tasks in medical imaging. The success of U-net is evident in its widespread use in all major image modalities from CT scans and MRI to X-rays and microscopy. Furthermore, while U-net is largely a segmentation tool, there have been instances of the use of U-net in other applications. As the potential of U-net is still increasing, in this review we look at the various developments that have been made in the U-net architecture and provide observations on recent trends. We examine the various innovations that have been made in deep learning and discuss how these tools facilitate U-net. Furthermore, we look at image modalities and application areas where U-net has been applied.Comment: 42 pages, in IEEE Acces

U-net and its variants for medical image segmentation: A review of theory and applications

U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for segmentation tasks in medical imaging. The success of U-net is evident in its widespread use in nearly all major image modalities, from CT scans and MRI to Xrays and microscopy. Furthermore, while U-net is largely a segmentation tool, there have been instances of the use of U-net in other applications. Given that U-net’s potential is still increasing, this narrative literature review examines the numerous developments and breakthroughs in the U-net architecture and provides observations on recent trends. We also discuss the many innovations that have advanced in deep learning and discuss how these tools facilitate U-net. In addition, we review the different image modalities and application areas that have been enhanced by U-net

On the Indeterminates of Glaucoma:the Controversy of Arterial Blood Pressure and Retinal Perfusion

Glaucoma is a chronic eye disease characterized by thinning of the retina, death of ganglion cells, and progressive loss of vision, eventually leading to blindness. The prevalence of glaucoma is estimated at 1-3% of those over 40 years old. With a constantly aging population, this number is expected to increase significantly over the next 10 years. Even with treatment, about 15% of people with glaucoma currently develop residual vision or tunnel vision and eventually become blind or partially sighted. The mechanisms behind ganglion cell death are poorly understood. Elevated eye pressure is the main risk factor for glaucoma, but treatment in the form of medication, laser, or surgery can only slow the decline, not stop it. In addition, high intraocular pressure is neither necessary nor sufficient for the development of glaucoma, indicating the existence of other unknown risk factors. It has been established that the death of ganglion cells results in a decreased oxygen demand and a concomitant decrease in blood flow. However, there is also a hypothesis that reduced or unstable blood supply is not only a consequence, but also a cause of glaucoma. This is known as the ‘chicken-egg’ dilemma in glaucoma. It is supported by the observation that the risk of developing glaucoma is higher in people with very low blood pressure (sometimes even as a result of overtreatment of high blood pressure).This dissertation is an attempt to methodically examine whether blood pressure can be linked to changes in the retina that could suggest susceptibility to glaucoma. For this purpose, we analyze epidemiological data from the Groningen Longitudinal Glaucoma Study, we use advanced imaging techniques to model the microcirculation, and we describe its relationship with the neural structure and oxygen consumption of the retina. We provide evidence leaning towards the existence of a vascular component, likely pertinent to glaucoma