Jue Jiang | DeepAI

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Featured Co-authors

Saad Nadeem
32 publications
Donghoon Lee
17 publications
Harini Veeraraghavan
12 publications
Joseph O. Deasy
10 publications
Neelam Tyagi
6 publications
Andreas Rimner
6 publications
Pengpeng Zhang
5 publications
Yu-Chi Hu
4 publications
Sadegh R Alam
3 publications
Sean Berry
3 publications
Jason Hu
3 publications

∙ 10/25/2022

Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT

Method: ProRSeg was trained using 5-fold cross-validation with 110 T2-we...

0 Jue Jiang, et al. ∙

∙ 05/20/2022

Self-supervised 3D anatomy segmentation using self-distilled masked image transformer (SMIT)

Vision transformers, with their ability to more efficiently model long-r...

0 Jue Jiang, et al. ∙

∙ 01/26/2022

One shot PACS: Patient specific Anatomic Context and Shape prior aware recurrent registration-segmentation of longitudinal thoracic cone beam CTs

Image-guided adaptive lung radiotherapy requires accurate tumor and orga...

5 Jue Jiang, et al. ∙

∙ 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...

7 Jue Jiang, et al. ∙

∙ 06/16/2021

Deformation Driven Seq2Seq Longitudinal Tumor and Organs-at-Risk Prediction for Radiotherapy

Purpose: Radiotherapy presents unique challenges and clinical requiremen...

7 Donghoon Lee, et al. ∙

∙ 02/26/2021

Nested-block self-attention for robust radiotherapy planning segmentation

Although deep convolutional networks have been widely studied for head a...

1 Harini Veeraraghavan, et al. ∙

∙ 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...

6 Jue Jiang, et al. ∙

∙ 07/19/2020

Unified cross-modality feature disentangler for unsupervised multi-domain MRI abdomen organs segmentation

Our contribution is a unified cross-modality feature disentagling approa...

0 Jue Jiang, et al. ∙

∙ 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...

8 Jue Jiang, et al. ∙

∙ 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...

0 Hyemin Um, et al. ∙

∙ 09/11/2019

Local block-wise self attention for normal organ segmentation

We developed a new and computationally simple local block-wise self atte...

0 Jue Jiang, et al. ∙

∙ 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...

0 Jue Jiang, et al. ∙

∙ 02/01/2019

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 inv...

0 Peter Klages, et al. ∙

∙ 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 ...

12 Jue Jiang, et al. ∙

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