2.8k citations · 2.9k across the 16 of their papers we have counts for
19 papers
Understanding From Human Perspective: A Multi-agent System for Interactive Egocentric Medical Image Segmentation
Rongjun Ge, Dongyang Wang, Heng Zhu +3
Interactive egocentric medical image segmentation (IEMIS) plays an important role in smart-glasses-assisted medical image review, segmenting the medical targets a clinician refers…
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…
Human Gaze-based Dual Teacher Guidance Learning for Semi-Supervised Medical Image Segmentation
Rongjun Ge, Chong Wang, Yuxin Liu +10
In the field of medical image segmentation, the scarcity of labeled data poses a major challenge for existing models to accurately perceive target regions. Compared with manual ann…
MRI Contrast Enhancement Kinetics World Model
Jindi Kong, Yuting He, Cong Xia +2
Clinical MRI contrast acquisition suffers from inefficient information yield, which presents as a mismatch between the risky and costly acquisition protocol and the fixed and spars…
Vector Contrastive Learning For Pixel-Wise Pretraining In Medical Vision
Yuting He, Shuo Li
Contrastive learning (CL) has become a cornerstone of self-supervised pretraining (SSP) in foundation models, however, extending CL to pixel-wise representation, crucial for medica…
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…
Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentation
Yaolei Qi, Yuting He, Xiaoming Qi +2
Accurate segmentation of topological tubular structures, such as blood vessels and roads, is crucial in various fields, ensuring accuracy and efficiency in downstream tasks. Howeve…
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…
Segment Anything in Medical Images
Jun Ma, Yuting He, Feifei Li +3
Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, oft…
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…
FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification
Kai-Ni Wang, Yuting He, Shuaishuai Zhuang +6
Reliable automatic classification of colonoscopy images is of great significance in assessing the stage of colonic lesions and formulating appropriate treatment plans. However, it…
XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention
Jiacheng Shi, Yuting He, Youyong Kong +4
An effective backbone network is important to deep learning-based Deformable Medical Image Registration (DMIR), because it extracts and matches the features between two images to d…
MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation
Zhangfu Dong, Yuting He, Xiaoming Qi +5
The nature of thick-slice scanning causes severe inter-slice discontinuities of 3D medical images, and the vanilla 2D/3D convolutional neural networks (CNNs) fail to represent spar…
CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Compartments Segmentation on CT Images
Song Wang, Yuting He, Youyong Kong +7
Renal compartment segmentation on CT images targets on extracting the 3D structure of renal compartments from abdominal CTA images and is of great significance to the diagnosis and…
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…
Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images
Yuting He, Tiantian Li, Guanyu Yang +6
Deep learning-based medical image registration and segmentation joint models utilize the complementarity (augmentation data or weakly supervised data from registration, region cons…