The role of noise in denoising models for anomaly detection in medical images.
Antanas KascenasPedro SanchezPatrick SchrempfChaoyang WangWilliam ClackettShadia MikhaelJeremy P. VoiseyKeith A. GoatmanAlexander WeirNicolas PugeaultSotirios A. TsaftarisAlison Q. O'NeilPublished in: Medical Image Anal. (2023)
Keyphrases
- medical images
- anomaly detection
- denoising
- intrusion detection
- medical imaging
- medical image analysis
- anatomical structures
- mr images
- medical image segmentation
- anomalous behavior
- ct images
- deformable models
- magnetic resonance imaging
- image denoising
- detecting anomalies
- magnetic resonance images
- one class support vector machines
- data assimilation
- magnetic resonance
- image intensity
- imaging modalities
- detect anomalies
- intrusion detection system
- probabilistic model
- network intrusion detection
- network anomaly detection
- segmentation of medical images
- network traffic
- medical image retrieval
- image analysis
- pairwise
- object recognition
- detecting anomalous
- learning algorithm
- machine learning