24 citations · 51 across the 5 of their papers we have counts for
6 papers
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Effect of Prior-based Losses on Segmentation Performance: A Benchmark
Rosana El Jurdi, Caroline Petitjean, Veronika Cheplygina +2
Today, deep convolutional neural networks (CNNs) have demonstrated state-of-the-art performance for medical image segmentation, on various imaging modalities and tasks. Despite ear…
High-level Prior-based Loss Functions for Medical Image Segmentation: A Survey
Rosana El Jurdi, Caroline Petitjean, Paul Honeine +2
Today, deep convolutional neural networks (CNNs) have demonstrated state of the art performance for supervised medical image segmentation, across various imaging modalities and tas…
SegTHOR: Segmentation of Thoracic Organs at Risk in CT images
Z. Lambert, C. Petitjean, B. Dubray +1
In the era of open science, public datasets, along with common experimental protocol, help in the process of designing and validating data science algorithms; they also contribute…
Pattern Spotting in Historical Documents Using Convolutional Models
Ignacio Úbeda, Jose M. Saavedra, Stéphane Nicolas +2
Pattern spotting consists of searching in a collection of historical document images for occurrences of a graphical object using an image query. Contrary to object detection, no pr…
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
Dong Nie, Roger Trullo, Caroline Petitjean +2
Computed tomography (CT) is critical for various clinical applications, e.g., radiotherapy treatment planning and also PET attenuation correction. However, CT exposes radiation dur…