title: Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms.
abstract: Algorithms are presented for rapid, automatic, robust, adaptive, and accurate tracing of retinal vasculature and analysis of intersections and crossovers. This method improves upon prior work in several ways: 1) automatic adaptation from frame to frame without manual initialization/adjustment, with few tunable parameters; 2) robust operation on image sequences exhibiting natural variability, poor and varying imaging conditions, including over/under-exposure, low contrast, and artifacts such as glare; 3) does not require the vasculature to be connected, so it can handle partial views; and 4) operation is efficient enough for use on unspecialized hardware, and amenable to deadline-driven computing, being able to produce a rapidly and monotonically improving sequence of usable partial results. Increased computation can be traded for superior tracing performance. Its efficiency comes from direct processing on gray-level data without any preprocessing, and from processing only a minimally necessary fraction of pixels in an exploratory manner, avoiding low-level image-wide operations such as thresholding, edge detection, and morphological processing. These properties make the algorithm suited to real-time, on-line (live) processing and is being applied to computer-assisted laser retinal surgery.
authors.affiliation: Electrical and Computer Science Engineering Department, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA.
authors.forename: A
authors.initials: A
authors.lastname: Can
authors.forename: H
authors.initials: H
authors.lastname: Shen
authors.forename: J N
authors.initials: JN
authors.lastname: Turner
authors.forename: H L
authors.initials: HL
authors.lastname: Tanenbaum
authors.forename: B
authors.initials: B
authors.lastname: Roysam
mesh_terms: D000465:Algorithms; D000792:Angiography; D001331:Automation; D012171:Retinal Vessels