Blog Archives

Automatic detection of drusen associated with age-related macular degeneration in optical coherence tomography: a graph based approach

Automatic Segmentation and Classification of Brain Tumors based on Multisequence MRI Images with Deep Learning Methods

A dataflow execution engine for automatic visual inspection of production lines

Documentation-driven GUI development for integration of image processing libraries

Detection of defects on displays based on microscopic and optical coherence tomography examination

Dilated convolutions in retinal blood vessels segmentation

Adaptive feature recombination and recalibration for semantic segmentation: application to brain tumor segmentation in MRI

Automatic brain tumor grading from MRI data using convolutional neural networks and quality assessment

Drinking Water Quality Monitoring: An Alternative Approach to Microbial Contamination Events

Multi-stage Deep Layer Aggregation for Brain Tumor Segmentation

From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach

Adaptive Feature Recombination and Recalibration for Semantic Segmentation with Fully Convolutional Networks

Stroke lesion outcome prediction based on MRI imaging combined with clinical information

Retinal vessel segmentation based on Fully Convolutional Neural Networks

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation

Hierarchical brain tumour segmentation using extremely randomized trees

Prediction of Stroke Lesion at 90-Day Follow-Up by Fusing Raw DSC-MRI with Parametric Maps Using Deep Learning

Combining unsupervised and supervised learning for predicting the final stroke lesion

Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls

CMEMS