162 citations · 289 across the 14 of their papers we have counts for
14 papers
Medical Imaging AI Competitions Lack Fairness
Annika Reinke, Evangelia Christodoulou, Sthuthi Sadananda +34
Benchmarking competitions are central to the development of artificial intelligence (AI) in medical imaging, defining performance standards and shaping methodological progress. How…
Scaling Artificial Intelligence for Prostate Cancer Detection on MRI towards Organized Screening and Primary Diagnosis in a Global, Multiethnic Population (Study Protocol)
Anindo Saha, Joeran S. Bosma, Jasper J. Twilt +26
In this intercontinental, confirmatory study, we include a retrospective cohort of 22,481 MRI examinations (21,288 patients; 46 cities in 22 countries) to train and externally vali…
QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge
Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…
Deformable MRI Sequence Registration for AI-based Prostate Cancer Diagnosis
Alessa Hering, Sarah de Boer, Anindo Saha +6
The PI-CAI (Prostate Imaging: Cancer AI) challenge led to expert-level diagnostic algorithms for clinically significant prostate cancer detection. The algorithms receive biparametr…
Uncertainty-Aware Semi-Supervised Learning for Prostate MRI Zonal Segmentation
Matin Hosseinzadeh, Anindo Saha, Joeran Bosma +1
Quality of deep convolutional neural network predictions strongly depends on the size of the training dataset and the quality of the annotations. Creating annotations, especially f…
Medical diffusion on a budget: Textual Inversion for medical image generation
Bram de Wilde, Anindo Saha, Maarten de Rooij +2
Diffusion models for text-to-image generation, known for their efficiency, accessibility, and quality, have gained popularity. While inference with these systems on consumer-grade…