54 citations · 156 across the 6 of their papers we have counts for
7 papers
Deep Learning Based Dominant Index Lesion Segmentation for MR-guided Radiation Therapy of Prostate Cancer
Josiah Simeth, Jue Jiang, Anton Nosov +4
Dose escalation radiotherapy allows increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL), motivating the development of automated me…
Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT
Jue Jiang, Jun Hong, Kathryn Tringale +4
Method: ProRSeg was trained using 5-fold cross-validation with 110 T2-weighted MRI acquired at 5 treatment fractions from 10 different patients, taking care that same patient scans…
Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)
Jue Jiang, Neelam Tyagi, Kathryn Tringale +2
Vision transformers, with their ability to more efficiently model long-range context, have demonstrated impressive accuracy gains in several computer vision and medical image analy…
PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentation
Jue Jiang, Yu Chi Hu, Neelam Tyagi +5
We developed a new joint probabilistic segmentation and image distribution matching generative adversarial network (PSIGAN) for unsupervised domain adaptation (UDA) and multi-organ…
Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation
Jue Jiang, Jason Hu, Neelam Tyagi +4
Lung tumors, especially those located close to or surrounded by soft tissues like the mediastinum, are difficult to segment due to the low soft tissue contrast on computed tomograp…
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
Peter Klages, Ilyes Benslimane, Sadegh Riyahi +5
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 C…