170 citations · 517 across the 12 of their papers we have counts for
5 papers · 1 filter
A General Method to Incorporate Spatial Information into Loss Functions for GAN-based Super-resolution Models
Xijun Wang, Santiago López-Tapia, Alice Lucas +3
Generative Adversarial Networks (GANs) have shown great performance on super-resolution problems since they can generate more visually realistic images and video frames. However, t…
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation
Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina
Medical image segmentation is a challenging task, particularly due to inter- and intra-observer variability, even between medical experts. In this paper, we propose a novel model,…
Smooth Attention for Deep Multiple Instance Learning: Application to CT Intracranial Hemorrhage Detection
Yunan Wu, Francisco M. Castro-Macías, Pablo Morales-Álvarez +2
Multiple Instance Learning (MIL) has been widely applied to medical imaging diagnosis, where bag labels are known and instance labels inside bags are unknown. Traditional MIL assum…
Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection
Julio Silva-Rodríguez, Adrián Colomer, María A. Sales +2
The Gleason scoring system is the primary diagnostic and prognostic tool for prostate cancer. In recent years, with the development of digitisation devices, the use of computer vis…
Self-supervised Fine-tuning for Correcting Super-Resolution Convolutional Neural Networks
Alice Lucas, Santiago Lopez-Tapia, Rafael Molina +1
While Convolutional Neural Networks (CNNs) trained for image and video super-resolution (SR) regularly achieve new state-of-the-art performance, they also suffer from significant d…