1.1k citations · 1.5k across the 13 of their papers we have counts for
15 papers · 1 filter
SurfR: Surface Reconstruction with Multi-scale Attention
Siddhant Ranade, Gonçalo Dias Pais, Ross Tyler Whitaker +3
We propose a fast and accurate surface reconstruction algorithm for unorganized point clouds using an implicit representation. Recent learning methods are either single-object repr…
Correspondence Free Multivector Cloud Registration using Conformal Geometric Algebra
Francisco Xavier Vasconcelos, Jacinto C. Nascimento
We present, for the first time, a novel theoretical approach to address the problem of correspondence free multivector cloud registration in conformal geometric algebra. Such forma…
Latent Embedding Clustering for Occlusion Robust Head Pose Estimation
José Celestino, Manuel Marques, Jacinto C. Nascimento
Head pose estimation has become a crucial area of research in computer vision given its usefulness in a wide range of applications, including robotics, surveillance, or driver atte…
2D Image head pose estimation via latent space regression under occlusion settings
José Celestino, Manuel Marques, Jacinto C. Nascimento +1
Head orientation is a challenging Computer Vision problem that has been extensively researched having a wide variety of applications. However, current state-of-the-art systems stil…
Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images
Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento +1
Survival time prediction from medical images is important for treatment planning, where accurate estimations can improve healthcare quality. One issue affecting the training of sur…
Post-hoc Overall Survival Time Prediction from Brain MRI
Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento +1
Overall survival (OS) time prediction is one of the most common estimates of the prognosis of gliomas and is used to design an appropriate treatment planning. State-of-the-art (SOT…
Region Proposals for Saliency Map Refinement for Weakly-supervised Disease Localisation and Classification
Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento +1
The deployment of automated systems to diagnose diseases from medical images is challenged by the requirement to localise the diagnosed diseases to justify or explain the classific…
Unsupervised Task Design to Meta-Train Medical Image Classifiers
Gabriel Maicas, Cuong Nguyen, Farbod Motlagh +2
Meta-training has been empirically demonstrated to be the most effective pre-training method for few-shot learning of medical image classifiers (i.e., classifiers modeled with smal…
3DRegNet: A Deep Neural Network for 3D Point Registration
G. Dias Pais, Srikumar Ramalingam, Venu Madhav Govindu +3
We present 3DRegNet, a novel deep learning architecture for the registration of 3D scans. Given a set of 3D point correspondences, we build a deep neural network to address the fol…
OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras
G. Dias Pais, Tiago J. Dias, Jacinto C. Nascimento +1
Pedestrian detection is one of the most explored topics in computer vision and robotics. The use of deep learning methods allowed the development of new and highly competitive algo…
Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification
Marc Combalia, Veronica Vilaplana
We propose a patch sampling strategy based on a sequential Monte-Carlo method for high resolution image classification in the context of Multiple Instance Learning. When compared w…
Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI
Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento +2
We propose a new method for breast cancer screening from DCE-MRI based on a post-hoc approach that is trained using weakly annotated data (i.e., labels are available only at the im…
Training Medical Image Analysis Systems like Radiologists
Gabriel Maicas, Andrew P. Bradley, Jacinto C. Nascimento +2
The training of medical image analysis systems using machine learning approaches follows a common script: collect and annotate a large dataset, train the classifier on the training…
Domain-adversarial neural networks to address the appearance variability of histopathology images
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof +2
Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters. The parameters can vary between pathology labs and within the same lab…
Automated 5-year Mortality Prediction using Deep Learning and Radiomics Features from Chest Computed Tomography
Gustavo Carneiro, Luke Oakden-Rayner, Andrew P. Bradley +2
We propose new methods for the prediction of 5-year mortality in elderly individuals using chest computed tomography (CT). The methods consist of a classifier that performs this pr…