Fundus Image Mosaicking for Information Augmentation in Computer-Assisted Slit-Lamp Imaging

Laser photocoagulation is currently the standard treatment for sight-threatening diseases worldwide, namely diabetic retinopathy and retinal vein occlusions. The slit lamp biomicroscope is the most commonly used device for this procedure, specially for the treatment of the eye periphery. However, only a small portion of the retina can be visualized through the biomicroscope, complicating the task of localizing and identifying surgical targets, increasing treatment duration and patient discomfort. In order to assist surgeons, we propose a method for creating intraoperative retina maps for view expansion using a slit-lamp device. Based on the mosaicking method described by Richa et al., 2012, the proposed method is a combination of direct and feature-based methods, suitable for the textured nature of the human retina. In this paper, we describe three major enhancements to the original formulation. The first is a visual tracking method using local illumination compensation to cope with the challenging visualization conditions. The second is an efficient pixel selection scheme for increased computational efficiency. The third is an entropy-based mosaic update method to dynamically improve the retina map during exploration. To evaluate the performance of the proposed method, we conducted several experiments on human subjects with a computer-assisted slit-lamp prototype. We also demonstrate the practical value of the system for photo documentation, diagnosis and intraoperative navigation.