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Found 6 papers, 1 papers with code
Unsupervised Domain Transfer with Conditional Invertible Neural Networks
Synthetic medical image generation has evolved as a key technique for neural network training and validation.
Robust deep learning-based semantic organ segmentation in hyperspectral images
To address this gap in the literature, we are investigating the following research questions based on hyperspectral imaging (HSI) data of pigs acquired in an open surgery setting: (1) What is an adequate representation of HSI data for neural network-based fully automated organ segmentation, especially with respect to the spatial granularity of the data (pixels vs. superpixels vs. patches vs. full images)?
Machine learning-based analysis of hyperspectral images for automated sepsis diagnosis
Sepsis is a leading cause of mortality and critical illness worldwide.
Video-rate multispectral imaging in laparoscopic surgery: First-in-human application
Multispectral and hyperspectral imaging (MSI/HSI) can provide clinically relevant information on morphological and functional tissue properties.
Out of distribution detection for intra-operative functional imaging
Multispectral optical imaging is becoming a key tool in the operating room.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks
Assessment of the specific hardware used in conjunction with such algorithms, however, has not properly addressed the possibility that the problem may be ill-posed.
