research
∙
07/16/2021
Unpaired cross-modality educed distillation (CMEDL) applied to CT lung tumor segmentation
Accurate and robust segmentation of lung cancers from CTs is needed to m...
share
research
∙
02/26/2021
Nested-block self-attention for robust radiotherapy planning segmentation
Although deep convolutional networks have been widely studied for head a...
research
∙
02/17/2021
Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation
Despite the widespread availability of in-treatment room cone beam compu...
research
∙
07/18/2020
PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentation
We developed a new joint probabilistic segmentation and image distributi...
research
∙
05/27/2020
Multiple resolution residual network for automatic thoracic organs-at-risk segmentation from CT
We implemented and evaluated a multiple resolution residual network (MRR...
research
∙
09/10/2019
Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation
Lung tumors, especially those located close to or surrounded by soft tis...
research
∙
05/22/2019
Kernel Wasserstein Distance
The Wasserstein distance is a powerful metric based on the theory of opt...
research
∙
01/31/2019
Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets
Lack of large expert annotated MR datasets makes training deep learning ...
research
∙
08/24/2018
Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response
Quantification of local metabolic tumor volume (MTV) chan-ges after Chem...
research
∙
08/24/2018
