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Found 4 papers, 3 papers with code
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
We further investigate the per-voxel segmentation performance of pancreatic tumors if AI is trained on a combination of CT scans with synthetic tumors and CT scans with annotated large tumors at an advanced stage.
Label-Free Liver Tumor Segmentation
We demonstrate that AI models can accurately segment liver tumors without the need for manual annotation by using synthetic tumors in CT scans.
Ranked #1 on
Tumor Segmentation
on LiTS17
Synthetic Tumors Make AI Segment Tumors Better
We develop a novel strategy to generate synthetic tumors.
Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
(2) The sampled deep vertex features with positional embedding are mapped into a sequential space and decoded by a multilayer perceptron (MLP) for semantic classification.
