Search Results for author:
Found 5 papers, 4 papers with code
CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation
The analysis shows that the performance of DL models for single modality (CT / MR) can show reliable volumetric analysis performance (DICE: 0. 98 $\pm$ 0. 00 / 0. 95 $\pm$ 0. 01) but the best MSSD performance remain limited (21. 89 $\pm$ 13. 94 / 20. 85 $\pm$ 10. 63 mm).
Dual Skip Connections Minimize the False Positive Rate of Lung Nodule Detection in CT images
Pulmonary cancer is one of the most commonly diagnosed and fatal cancers and is often diagnosed by incidental findings on computed tomography.
Sinogram upsampling using Primal-Dual UNet for undersampled CT and radial MRI reconstruction
However, the undersampled reconstruction problem for these two modalities was always considered as two different problems and tackled separately by different research works.
Dual Branch Prior-SegNet: CNN for Interventional CBCT using Planning Scan and Auxiliary Segmentation Loss
This paper proposes an extension to the Dual Branch Prior-Net for sparse view interventional CBCT reconstruction incorporating a high quality planning scan.
Primal-Dual UNet for Sparse View Cone Beam Computed Tomography Volume Reconstruction
In this paper, the Primal-Dual UNet for sparse view CT reconstruction is modified to be applicable to cone beam projections and perform reconstructions of entire volumes instead of slices.
