Detection of lesions in retina photographs based on the wavelet transform.
In this article, we propose an automatic diabetic retinopathy screening method. In particular, we focus on detecting microaneurysms in retina photographs, as they are the most common and first appearing lesions in the disease development. This is done by matching a lesion template in the wavelet domain, using the sum of the squared errors as a criterion on some decomposition subbands. The method outperforms classification methods in the wavelet domain, which seem unfitted to describe small structures shapes. More, it could be generalized to other small lesions. Results are evaluated on a manually segmented retinal images database for different usual mother wavelets.
Quellec
Gwénolé
G
Lab. de Traitement de l'Inf. Medicale Inserm, CHU, Brest, France. gwenole.quellec@enst-bretagne.fr
Lamard
Mathieu
M
Josselin
Pierre Marie
PM
Cazuguel
Guy
G
Cochener
Béatrice
B
Roux
Christian
C
D000465:Algorithms; D000783:Aneurysm / Q000473:pathology*; D001185:Artificial Intelligence; D003930:Diabetic Retinopathy / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012161:Retinal Artery / Q000473:pathology*; D042262:Retinoscopy / Q000379:methods*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted