19 citations · 21 across the 5 of their papers we have counts for
5 papers
Nodule detection and generation on chest X-rays: NODE21 Challenge
Ecem Sogancioglu, Bram van Ginneken, Finn Behrendt +16
Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep lea…
Joint Supervised and Self-supervised Learning for MRI Reconstruction
George Yiasemis, Nikita Moriakov, Clara I. Sánchez +2
Magnetic Resonance Imaging (MRI) represents an important diagnostic modality; however, its inherently slow acquisition process poses challenges in obtaining fully-sampled -space…
AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge
Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard +33
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effectiv…
Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography
Coen de Vente, Bram van Ginneken, Carel B. Hoyng +2
Deep learning classification models for medical image analysis often perform well on data from scanners that were used during training. However, when these models are applied to da…
On Retrospective k-space Subsampling schemes For Deep MRI Reconstruction
George Yiasemis, Clara I. Sánchez, Jan-Jakob Sonke +1
Acquiring fully-sampled MRI -space data is time-consuming, and collecting accelerated data can reduce the acquisition time. Employing 2D Cartesian-rectilinear subsampling scheme…