2

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
We used epistemic uncertainty estimates to discover potential abnormalities in diseased OCT scans. The uncertainty maps are obtained by a Bayesian U-Net trained on healthy OCT scans with weak labels of the retinal layers.
Philipp Seeböck, José Ignacio Orlando, Thomas Schlegl, Sebastian M. Waldstein, Hrvoje Bogunović, Sophie Klimscha, Georg Langs, Ursula Schmidt-Erfurth
PDF Cite DOI
An ensemble deep learning based approach for red lesion detection in fundus images
We introduced a hybrid red lesion detection model based on a combination of deep learning based features and hand crafted descriptors.
José Ignacio Orlando, Elena Prokofyeva, Mariana Del Fresno, Matthew B. Blaschko
PDF Cite Code DOI
Proliferative diabetic retinopathy characterization based on fractal features: Evaluation on a publicly available dataset
We develop a fractal based model for detecting proliferative diabetic retinopathy cases from fundus pictures.
José Ignacio Orlando, Karel Van Keer, João Barbosa Breda, Hugo Luis Manterola, Matthew B Blaschko, Alejandro Clausse
PDF Cite Code Dataset DOI
A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images
We present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained fully connected conditional random field model.
José Ignacio Orlando, Elena Prokofyeva, Matthew B Blaschko
PDF Cite Code Project DOI
Assessment of image features for vessel wall segmentation in intravascular ultrasound images
We explored and evaluated different feature extraction techniques in the context of IVUS segmentation.
Lucas Lo Vercio, José Ignacio Orlando, Mariana Del Fresno, Ignacio Larrabide
PDF Cite Project DOI
Reviewing Preprocessing and Feature Extraction Techniques for Retinal Blood Vessels Segmentation in Fundus Images
We explored and evaluated different feature extraction techniques in the context of retinal blood segmentation with SVMs.
José Ignacio Orlando, Mariana Del Fresno
PDF Cite