Segmentation
Segmentation, in the context of informatics for radiology, refers to the delineation of an areas of interest in imaging in terms of pixels or voxels. Segmentation is often accomplished by computerized algorithms that vary in complexity from simply selecting pixels of similar values in proximity to those that include radiometric features or are based on machine learning. Segmentation is usually a necessary step in creating modifiable three dimensional images for surface modeling and/or medical printing from imaging.
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Artificial intelligence
- artificial intelligence (AI)
- imaging data sets
- computer-aided diagnosis (CAD)
- natural language processing
- machine learning (overview)
- visualizing and understanding neural networks
- common data preparation/preprocessing steps
- DICOM to bitmap conversion
- dimensionality reduction
- scaling
- centering
- normalization
- principal component analysis
- training, testing and validation datasets
- augmentation
- loss function
-
optimization algorithms
- ADAM
- momentum (Nesterov)
- stochastic gradient descent
- mini-batch gradient descent
-
regularisation
- linear and quadratic
- batch normalization
- ensembling
- rule-based expert systems
- glossary
- activation function
- anomaly detection
- automation bias
- backpropagation
- batch size
- cost function
- confusion matrix
- convolution
- curse of dimensionality
- epoch
- gradient descent
- image registration
- imputation
- iteration
- linear algebra
- noise reduction
- R (Programming language)
- Python (Programming language)
- segmentation
- synthetic and augmented data
- overfitting
- transfer learning
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