Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models

Markus Ditlev Sjøgren Olsen; Jakob Ambsdorf; Manxi Lin; Caroline Taksøe‐Vester; Morten Bo Søndergaard Svendsen; Anders Nymark Christensen; Mads Nielsen; Martin G. Tolsgaard; Aasa Feragen; Paraskevas Pegios

doi:10.1007/978-3-031-73647-6_20

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Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models

Markus Ditlev Sjøgren Olsen Jakob Ambsdorf Manxi Lin Caroline Taksøe‐Vester Morten Bo Søndergaard Svendsen Anders Nymark Christensen Mads Nielsen Martin G. Tolsgaard Aasa Feragen Paraskevas Pegios

Year: 2024 Lecture notes in computer science Pages: 209-219 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-73647-6_20

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Keywords:

Computer science Anomaly detection Artificial intelligence Abnormality Pattern recognition (psychology) Noise (video) Noise reduction Anomaly (physics) Medicine Image (mathematics)

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Fetal and Pediatric Neurological Disorders

Health Sciences → Medicine → Pediatrics, Perinatology and Child Health

Domain Adaptation and Few-Shot Learning

Physical Sciences → Computer Science → Artificial Intelligence

Generative Adversarial Networks and Image Synthesis

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models

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