title: Detection of lesions in retina photographs based on the wavelet transform.
abstract: 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.
authors.affiliation: Lab. de Traitement de l'Inf. Medicale Inserm, CHU, Brest, France. gwenole.quellec@enst-bretagne.fr
authors.forename: Gwénolé
authors.initials: G
authors.lastname: Quellec
authors.forename: Mathieu
authors.initials: M
authors.lastname: Lamard
authors.forename: Pierre Marie
authors.initials: PM
authors.lastname: Josselin
authors.forename: Guy
authors.initials: G
authors.lastname: Cazuguel
authors.forename: Béatrice
authors.initials: B
authors.lastname: Cochener
authors.forename: Christian
authors.initials: C
authors.lastname: Roux
mesh_terms: 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