4 citations · 9 across the 13 of their papers we have counts for
14 papers
From Data Completeness to Data Sufficiency: A Task-Driven Imaging Framework for Intraoperative CBCT under Quality-Time-Dose Trade-offs
Yi Jia, Rongjun Ge, Yang Chen +2
Mobile C-arm cone-beam computed tomography (CBCT) has been widely used for real-time intraoperative 3D imaging. However, current practice often mechanically applies the fan-beam CT…
RelativeFlow: Taming Medical Image Denoising Learning with Noisy Reference
Yuxin Liu, Yiqing Dong, Wenxue Yu +4
Medical image denoising (MID) lacks absolutely clean images for supervision, leading to a noisy reference problem that fundamentally limits denoising performance. Existing simulate…
Generative Data-engine Foundation Model for Universal Few-shot 2D Vascular Image Segmentation
Rongjun Ge, Xin Li, Yuxing Liu +8
The segmentation of 2D vascular structures via deep learning holds significant clinical value but is hindered by the scarcity of annotated data, severely limiting its widespread ap…
VCC-DSA: A Novel Vascular Consistency Constrained DSA Imaging Model for Motion Artifact Suppression
Rongjun Ge, Weilong Mao, Jian Lu +9
Digital Subtraction Angiography (DSA) is a clinically significant imaging technique for diagnosing cerebrovascular disease, as gold-standard. However, the artifacts caused by motio…
DINO-BOLDNet: A DINOv3-Guided Multi-Slice Attention Network for T1-to-BOLD Generation
Jianwei Wang, Qing Wang, Menglan Ruan +4
Generating BOLD images from T1w images offers a promising solution for recovering missing BOLD information and enabling downstream tasks when BOLD images are corrupted or unavailab…
Think as Cardiac Sonographers: Marrying SAM with Left Ventricular Indicators Measurements According to Clinical Guidelines
Tuo Liu, Qinghan Yang, Yu Zhang +3
Left ventricular (LV) indicator measurements following clinical echocardiog-raphy guidelines are important for diagnosing cardiovascular disease. Alt-hough existing algorithms have…
Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learning
Yuting He, Boyu Wang, Rongjun Ge +3
Dense contrastive representation learning (DCRL) has greatly improved the learning efficiency for image-dense prediction tasks, showing its great potential to reduce the large cost…
Gaze-Assisted Human-Centric Domain Adaptation for Cardiac Ultrasound Image Segmentation
Ruiyi Li, Yuting He, Rongjun Ge +4
Domain adaptation (DA) for cardiac ultrasound image segmentation is clinically significant and valuable. However, previous domain adaptation methods are prone to be affected by the…
Imaging foundation model for universal enhancement of non-ideal measurement CT
Rongjun Ge, Yuxin Liu, Zhan Wu +7
Non-ideal measurement computed tomography (NICT) employs suboptimal imaging protocols to expand CT applications. However, the resulting trade-offs degrade image quality, limiting c…
Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training
Xiaofei Chen, Yuting He, Cheng Xue +3
The foundation models based on pre-training technology have significantly advanced artificial intelligence from theoretical to practical applications. These models have facilitated…
JCCS-PFGM: A Novel Circle-Supervision based Poisson Flow Generative Model for Multiphase CECT Progressive Low-Dose Reconstruction with Joint Condition
Rongjun Ge, Yuting He, Cong Xia +3
Multiphase contrast-enhanced computed tomography (CECT) scan is clinically significant to demonstrate the anatomy at different phases. In practice, such a multiphase CECT scan inhe…
Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training
Yuting He, Guanyu Yang, Rongjun Ge +4
Learning inter-image similarity is crucial for 3D medical images self-supervised pre-training, due to their sharing of numerous same semantic regions. However, the lack of the sema…
Low-Dose CT Denoising via Sinogram Inner-Structure Transformer
Liutao Yang, Zhongnian Li, Rongjun Ge +3
Low-Dose Computed Tomography (LDCT) technique, which reduces the radiation harm to human bodies, is now attracting increasing interest in the medical imaging field. As the image qu…
EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
Yuting He, Rongjun Ge, Xiaoming Qi +6
3D complete renal structures(CRS) segmentation targets on segmenting the kidneys, tumors, renal arteries and veins in one inference. Once successful, it will provide preoperative p…