A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification
The eye affords a unique opportunity to inspect a rich part of the human microvasculature
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …
non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are …
Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets
Every year, millions of brain MRI scans are acquired in hospitals, which is a figure
considerably larger than the size of any research dataset. Therefore, the ability to analyze …
considerably larger than the size of any research dataset. Therefore, the ability to analyze …
Synthesize then compare: Detecting failures and anomalies for semantic segmentation
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Recent developments in artificial intelligence have generated increasing interest to deploy
automated image analysis for diagnostic imaging and large-scale clinical applications …
automated image analysis for diagnostic imaging and large-scale clinical applications …
Reverse classification accuracy: predicting segmentation performance in the absence of ground truth
When integrating computational tools, such as automatic segmentation, into clinical practice,
it is of utmost importance to be able to assess the level of accuracy on new data and, in …
it is of utmost importance to be able to assess the level of accuracy on new data and, in …