Automatic characterization of classic choroidal neovascularization by using AdaBoost for supervised learning.
OBJECTIVE
To provide a computer-aided visualization tool for accurate diagnosis and quantification of choroidal neovascularization (CNV) on the basis of fluorescence leakage characteristics.


METHODS
All image frames of a fluorescein angiography (FA) sequence are first aligned and mapped to a global space. To automatically determine the severity of each pixel in the global space and hence the extent of CNV, the system matches the intensity variation of each set of spatially corresponding pixels across the sequence with the targeted leakage pattern, learned from a sampled population graded by a retina specialist. The learning strategy, known as the AdaBoost algorithm, has 12 classifiers for 12 features that summarize the variation in fluorescence intensity over time. Given a new sequence, the severity map image is generated using the contribution scores of the 12 classifiers. Initialized with points of low and high severity, regions of CNV are delineated using the random walk algorithm.


RESULTS
A dataset of 33 FA sequences of classic CNV showed the average accuracy of CNV delineation to be 83.26%. In addition, the 30- to 60-second interval provided the most reliable information for differentiating CNV from the background. Using eight sequences of multiple visits of four patients for evaluation of the postphotodynamic therapy (PDT), the statistics derived from the segmented regions correlate closely with the clinical observed changes.


CONCLUSIONS
The clinician can easily visualize the temporal characteristics of CNV fluorescence leakage using the severity map, which is a two-dimensional summary of a complete FA sequence. The computer-aided tool allows objective evaluation and computation of statistical data from the automatic delineation for surgical assessment.
Computer Science Department, Iona College, New Rochelle, New York, USA.
Chia-Ling
CL
Tsai
Yi-Lun
YL
Yang
Shih-Jen
SJ
Chen
Kai-Shung
KS
Lin
Chih-Hao
CH
Chan
Wei-Yang
WY
Lin
D000465:Algorithms; D002199:Capillary Permeability; D002829:Choroid / Q000098:blood supply; D020256:Choroidal Neovascularization / Q000145:classification / Q000175:diagnosis* / Q000188:drug therapy; D003936:Diagnosis, Computer-Assisted / Q000145:classification*; D005451:Fluorescein Angiography; D006801:Humans; D010778:Photochemotherapy; D015203:Reproducibility of Results