Search Results for author: Xuanang Xu

Found 10 papers, 6 papers with code

General Purpose Image Encoder DINOv2 for Medical Image Registration

no code implementations24 Feb 2024 Xinrui Song, Xuanang Xu, Pingkun Yan

In this paper, we present a training-free deformable image registration method, DINO-Reg, leveraging a general purpose image encoder DINOv2 for image feature extraction.

Image Registration Medical Image Registration

Soft-tissue Driven Craniomaxillofacial Surgical Planning

no code implementations20 Jul 2023 Xi Fang, Daeseung Kim, Xuanang Xu, Tianshu Kuang, Nathan Lampen, Jungwook Lee, Hannah H. Deng, Jaime Gateno, Michael A. K. Liebschner, James J. Xia, Pingkun Yan

Our framework consists of a bony planner network that estimates the bony movements required to achieve the desired facial outcome and a facial simulator network that can simulate the possible facial changes resulting from the estimated bony movement plans.

Distance Map Supervised Landmark Localization for MR-TRUS Registration

no code implementations11 Oct 2022 Xinrui Song, Xuanang Xu, Sheng Xu, Baris Turkbey, Bradford J. Wood, Thomas Sanford, Pingkun Yan

We then use the predicted landmarks to generate the affine transformation matrix, which outperforms the clinicians' manual rigid registration by a significant margin in terms of TRE.

Image Registration

Deep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement

no code implementations4 Oct 2022 Xi Fang, Daeseung Kim, Xuanang Xu, Tianshu Kuang, Hannah H. Deng, Joshua C. Barber, Nathan Lampen, Jaime Gateno, Michael A. K. Liebschner, James J. Xia, Pingkun Yan

In this work, we propose an Attentive Correspondence assisted Movement Transformation network (ACMT-Net) to estimate the facial appearance by transforming the bony movement to facial soft tissue through a point-to-point attentive correspondence matrix.

Computational Efficiency

Federated Multi-organ Segmentation with Inconsistent Labels

1 code implementation14 Jun 2022 Xuanang Xu, Hannah H. Deng, Jaime Gateno, Pingkun Yan

Extensive experiments on six public abdominal CT datasets show that our Fed-MENU method can effectively obtain a federated learning model using the partially labeled datasets with superior performance to other models trained by either localized or centralized learning methods.

Federated Learning Organ Segmentation +1

Federated Cross Learning for Medical Image Segmentation

1 code implementation5 Apr 2022 Xuanang Xu, Hannah H. Deng, Tianyi Chen, Tianshu Kuang, Joshua C. Barber, Daeseung Kim, Jaime Gateno, James J. Xia, Pingkun Yan

In this paper, we first conduct a theoretical analysis on the FL algorithm to reveal the problem of model aggregation during training on non-iid data.

Ensemble Learning Federated Learning +3

End-to-end Ultrasound Frame to Volume Registration

1 code implementation14 Jul 2021 Hengtao Guo, Xuanang Xu, Sheng Xu, Bradford J. Wood, Pingkun Yan

Fusing intra-operative 2D transrectal ultrasound (TRUS) image with pre-operative 3D magnetic resonance (MR) volume to guide prostate biopsy can significantly increase the yield.

Cross-modal Attention for MRI and Ultrasound Volume Registration

1 code implementation9 Jul 2021 Xinrui Song, Hengtao Guo, Xuanang Xu, Hanqing Chao, Sheng Xu, Baris Turkbey, Bradford J. Wood, Ge Wang, Pingkun Yan

In the past few years, convolutional neural networks (CNNs) have been proved powerful in extracting image features crucial for image registration.

Image Registration

Task-Oriented Low-Dose CT Image Denoising

1 code implementation25 Mar 2021 Jiajin Zhang, Hanqing Chao, Xuanang Xu, Chuang Niu, Ge Wang, Pingkun Yan

The extensive use of medical CT has raised a public concern over the radiation dose to the patient.

Image Denoising

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