Subject(s)
Certification/standards , Total Quality Management , Germany , Humans , Insurance, Health/standardsABSTRACT
AIMS: To process video slit lamp biomicroscopic fundus image sequences in order to generate wide field, high quality fundus image montages which might be suitable for photodocumentation. METHODS: Slit lamp biomicroscopic fundus examination was performed on human volunteers with a contact or non-contact lens. A stock, charge coupled device camera permitted image capture and storage of the image sequence at 30 frames per second. Acquisition time was approximately 30 seconds. Individual slit lamp biomicroscope fundus image frames were aligned and blended with custom developed software. RESULTS: The developed algorithms allowed for highly accurate alignment and blending of partially overlapping slit lamp biomicroscopic fundus images to generate a seamless, high quality, wide field montage. CONCLUSIONS: Video image acquisition and processing algorithms allow for mosaicking and enhancement of slit lamp biomicroscopic fundus images. The improved quality and wide field of view may confer suitability for inexpensive, real time photodocumentation of disc and macular abnormalities.
Subject(s)
Image Processing, Computer-Assisted , Ophthalmoscopy/methods , Algorithms , Humans , Software , Video RecordingABSTRACT
We present a validation study of an optical-flow method for the rapid estimation of myocardial displacement in magnetic resonance tagged cardiac images. This registration and change visualization (RCV) software uses a hierarchical estimation technique to compute the flow field that describes the warping of an image of one cardiac phase into alignment with the next. This method overcomes the requirement of constant pixel intensity in standard optical-flow methods by preprocessing the input images to reduce any intensity bias which results from the reduction in stripe contrast throughout the cardiac cycle. To validate the method, SPAMM-tagged images were acquired of a silicon gel phantom with simulated rotational motion. The pixel displacement was estimated with the RCV method and the error in pixel tracking was <4% 1000 ms after application of the tags, and after 30 degrees of rotation. An additional study was performed using a SPAMM-tagged multiphase slice of a canine left ventricle. The true displacement was determined using a previously validated active contour model (snakes). The error between methods was 6.7% at end systole. The RCV method has the advantage of tracking all pixels in the image in a substantially shorter period than the snakes method.
