5 papers
Ultrasound-CLIP: Semantic-Aware Contrastive Pre-training for Ultrasound Image-Text Understanding
Jiayun Jin, Haolong Chai, Xueying Huang +7
Ultrasound imaging is widely used in clinical diagnostics due to its real-time capability and radiation-free nature. However, existing vision-language pre-training models, such as…
IterMask3D: Unsupervised Anomaly Detection and Segmentation with Test-Time Iterative Mask Refinement in 3D Brain MR
Ziyun Liang, Xiaoqing Guo, Wentian Xu +5
Unsupervised anomaly detection and segmentation methods train a model to learn the training distribution as `normal'. In the testing phase, they identify patterns that deviate from…
MMSummary: Multimodal Summary Generation for Fetal Ultrasound Video
Xiaoqing Guo, Qianhui Men, J. Alison Noble
We present the first automated multimodal summary generation system, MMSummary, for medical imaging video, particularly with a focus on fetal ultrasound analysis. Imitating the exa…
Pose-GuideNet: Automatic Scanning Guidance for Fetal Head Ultrasound from Pose Estimation
Qianhui Men, Xiaoqing Guo, Aris T. Papageorghiou +1
3D pose estimation from a 2D cross-sectional view enables healthcare professionals to navigate through the 3D space, and such techniques initiate automatic guidance in many image-g…
IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI
Ziyun Liang, Xiaoqing Guo, J. Alison Noble +1
Unsupervised anomaly segmentation approaches to pathology segmentation train a model on images of healthy subjects, that they define as the 'normal' data distribution. At inference…