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Found 7 papers, 2 papers with code
Deep Learning Based Dominant Index Lesion Segmentation for MR-guided Radiation Therapy of Prostate Cancer
MRRN-DS significantly outperformed ResUnet in Dataset2 (DSC of 0. 54 vs. 0. 44, p<0. 001) and the Unet++ in Dataset3 (DSC of 0. 45 vs. p=0. 04).
Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT
ProRSeg based dose accumulation accounting for intra-fraction (pre-treatment to post-treatment MRI scan) and inter-fraction motion showed that the organ dose constraints were violated in 4 patients for stomach-duodenum and for 3 patients for small bowel.
Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)
Self-supervised learning (SSL) has demonstrated success in medical image segmentation using convolutional networks.
PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentation
Our method achieved an overall average DSC of 0. 87 on T1w and 0. 90 on T2w for the abdominal organs, 0. 82 on T2wFS for the parotid glands, and 0. 77 on T2w MRI for lung tumors.
Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation
Our approach, called cross-modality educed deep learning segmentation (CMEDL) combines CT and pseudo MR produced from CT by aligning their features to obtain segmentation on CT.
Comparison of Patch-Based Conditional Generative Adversarial Neural Net Models with Emphasis on Model Robustness for Use in Head and Neck Cases for MR-Only planning
A total of twenty paired CT and MR images were used in this study to investigate two conditional generative adversarial networks, Pix2Pix, and Cycle GAN, for generating synthetic CT images for Headand Neck cancer cases.
Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets
This method produced the highest segmentation accuracy with a DSC of 0. 75 and the lowest Hausdroff distance on the test dataset.
