4 papers
Annotating anatomy and pathology in the National Lung Screening Trial computed tomography images
Deepa Krishnaswamy, Vamsi Thiriveedhi, Suraj Pai +6
Large-scale public medical imaging datasets contribute critically to translational research. When accompanied by rich clinical and multi-omics data, they can stimulate exploratory…
In search of truth: Evaluating concordance of AI-based anatomy segmentation models
Lena Giebeler, Deepa Krishnaswamy, David Clunie +9
Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the cha…
Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation
Deepa Krishnaswamy, Cosmin Ciausu, Steve Pieper +3
Recent advances in deep learning have led to robust automated tools for segmentation of abdominal computed tomography (CT). Meanwhile, segmentation of magnetic resonance imaging (M…
Rule-based outlier detection of AI-generated anatomy segmentations
Deepa Krishnaswamy, Vamsi Krishna Thiriveedhi, Cosmin Ciausu +4
There is a dire need for medical imaging datasets with accompanying annotations to perform downstream patient analysis. However, it is difficult to manually generate these annotati…