2

On Orthogonal Projections for Dimension Reduction and Applications in Augmented Target Loss Functions for Learning Problems

Anna introduced a new mathematical approach for dimensionality reduction that we incorporated into loss functions to augment target information and improve performance.

REFUGE challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs

This is the summary publication of the REFUGE challenge on glaucoma detection in color fundus photographs.

Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs

We applied CycleGANs to improve realism in ultrasound simulation based on ray-casting methods.

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.

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.

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.

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.

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.

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.