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

Abstract

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.

A comparative study of transformation models for the sequential mosaicing of long retinal sequences of slit-lamp images obtained in a closed-loop motion

“…We segment the visible part of the retina and filter out strong specularities using intensity thresholding and morphological operations [17]. We then detect and extract key points with scale invariant feature transform (SIFT) [15] and match them between consecutive frames.…”

“…Computer-assisted retina mosaicing for view expansion using a slit-lamp device has been recently proposed [17,18] and integrated in the slit-lamp system of QuantelMedical, France (Fig. 1a).…”

“…The objective is to find the parameters of a transformation model that aligns the reference image of a target object to its current image so that a chosen similarity measure between the two images is maximized. It is combined with feature-based tracking to perform re-initialization if the target is lost [17]. Retinal mosaics built with this method suffer from accumulated drift induced by sequential mapping (Fig.…”

EyeSLAM: Real‐time simultaneous localization and mapping of retinal vessels during intraocular microsurgery

“…Some methods use custom descriptors or match uniquely identifiable vessel locations such as bifurcations . Other methods match the shape of the entire vasculature tree between images . More recently, hybrid methods combine sparse keypoints with tracking on the pixel level to create a mosaic from a video in real time .…”

EnViSoRS: Enhanced Vision System for Robotic Surgery. A User-Defined Safety Volume Tracking to Minimize the Risk of Intraoperative Bleeding

“…In order to overcome these limitations and to update the preoperative/intraoperative registration at run-time, computer vision and image-based tracking algorithms can be exploited to track these areas relying on image characteristics (Stoyanov, 2012). Different attempts have been made in literature for soft tissue tracking in endoscopic images (Yip et al, 2012;Giannarou et al, 2013;Puerto-Souza et al, 2014;Richa et al, 2014). Furthermore, to track the region of interest in the 3D space and to have a more accurate knowledge of the tissue deformation, 3D reconstruction algorithms are exploited to reconstruct the surface of the surgical area (Stoyanov et al, 2010;Röhl et al, 2012;Maier-Hein et al, 2013.…”