15 citations · 27 across the 7 of their papers we have counts for
7 papers
Focused Active Learning for Histopathological Image Classification
Arne Schmidt, Pablo Morales-Álvarez, Lee A. D. Cooper +4
Active Learning (AL) has the potential to solve a major problem of digital pathology: the efficient acquisition of labeled data for machine learning algorithms. However, existing A…
Hyperbolic Secant representation of the logistic function: Application to probabilistic Multiple Instance Learning for CT intracranial hemorrhage detection
F. M. Castro-Macías, P. Morales-Álvarez, Y. Wu +2
Multiple Instance Learning (MIL) is a weakly supervised paradigm that has been successfully applied to many different scientific areas and is particularly well suited to medical im…
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…
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images
Pablo Morales-Álvarez, Arne Schmidt, José Miguel Hernández-Lobato +1
In the last years, the weakly supervised paradigm of multiple instance learning (MIL) has become very popular in many different areas. A paradigmatic example is computational patho…
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…