Search Results for author:
Found 14 papers, 0 papers with code
POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring
Semi-supervised learning (SSL) uses unlabeled data to compensate for the scarcity of annotated images and the lack of method generalization to unseen domains, two usual problems in medical segmentation tasks.
DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation
Instead of proposing another improvement of the segmentation accuracy, we propose a novel method robust to domain shift and performing well on unseen datasets, called DeepLesionBrain (DLB).
AssemblyNet: A large ensemble of CNNs for 3D Whole Brain MRI Segmentation
Finally, we showed the interest of using semi-supervised learning to improve the performance of our method.
Multi-scale Graph-based Grading for Alzheimer's Disease Prediction
Based on a cascade of classifiers, this multiscale approach enables the analysis of alterations of whole brain structures and hippocampus subfields at the same time.
AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation
Whole brain segmentation using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images.
Robust Shape Regularity Criteria for Superpixel Evaluation
Regular decompositions are necessary for most superpixel-based object recognition or tracking applications.
Evaluation Framework of Superpixel Methods with a Global Regularity Measure
To measure the regularity aspect, we propose a new global regularity measure (GR), which addresses the non-robustness of state-of-the-art metrics.
SuperPatchMatch: an Algorithm for Robust Correspondences using Superpixel Patches
Superpixels have become very popular in many computer vision applications.
Robust superpixels using color and contour features along linear path
During the decomposition, we propose to consider color features along the linear path between the pixel and the corresponding superpixel barycenter.
An Optimized PatchMatch for Multi-scale and Multi-feature Label Fusion
On the EADC-ADNI dataset, we compare the hippocampal volumes obtained by manual and automatic segmentation.
SCALP: Superpixels with Contour Adherence using Linear Path
In this paper, we propose a fast method to compute Superpixels with Contour Adherence using Linear Path (SCALP) in an iterative clustering framework.
Superpixel-based Color Transfer
In this work, we propose a fast superpixel-based color transfer method (SCT) between two images.
Texture-Aware Superpixel Segmentation
Most superpixel algorithms compute a trade-off between spatial and color features at the pixel level.
Graph of brain structures grading for early detection of Alzheimer's disease
Alzheimer's disease is the most common dementia leading to an irreversible neurodegenerative process.
