have studied retinal image registration in the context of the National
Institutes of Health (NIH), Early Treatment Diabetic Retinopathy Study (ETDRS)
standard protocol. The ETDRS protocol defines seven 30-degree fields of
each retina with specific field coverage. A robust ETDRS image
registration algorithm is required to (1) assess image quality in terms
of ETDRS field coverage, and to (2) support ETDRS-based disease staging.
Three major challenges are present. First, small overlaps between
adjacent fields lead to inadequate landmark points (crossovers and
bifurcations) for feature-based methods. Second, the contrast and
intensity distributions within an image are not spatially uniform or
consistent. This can deteriorate the performance of area-based
techniques. Third, high-resolution ETDRS images contain large
homogeneous nonvascular/textureless regions which result in difficulties
for both feature-based and area-based techniques. In this work, we
propose an ETDRS image registration algorithm which effectively combines
both area-based and
Retinal image registration example.
T. Chanwimaluang, G. Fan, and S. Fransen, “Hybrid
Retinal Image Registration”, IEEE Trans. on Information Technology in
Biomedicine, Vol. 10, No. 1, , pp129-142, Jan. 2006.
T. Chanwimaluang and G. Fan, “Retinal Image
Registration for NIH’s ETDRS", in Proc. International Symposium on
Visual Computing, Lake Tahoe, Nevada, Dec. 2005, also in LNCS, Vol.
3804, Editors: G. Bebis, Springer, 2005.