Clip in medical imaging: A comprehensive survey

Z Zhao, Y Liu, H Wu, M Wang, Y Li, S Wang… - arxiv preprint arxiv …, 2023 - arxiv.org
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training
paradigm, successfully introduces text supervision to vision models. It has shown promising …

[HTML][HTML] Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data

S Jecklin, Y Shen, A Gout, D Suter, L Calvet… - Medical Image …, 2024 - Elsevier
In this study, we address critical barriers hindering the widespread adoption of surgical
navigation in orthopedic surgeries due to limitations such as time constraints, cost …

Spineclue: Automatic vertebrae identification using contrastive learning and uncertainty estimation

S Zhang, M Chen, J Wu, Z Zhang, T Li, C Xue… - arxiv preprint arxiv …, 2024 - arxiv.org
Vertebrae identification in arbitrary fields-of-view plays a crucial role in diagnosing spine
disease. Most spine CT contain only local regions, such as the neck, chest, and abdomen …

Semantics and instance interactive learning for labeling and segmentation of vertebrae in CT images

Y Mao, Q Feng, Y Zhang, Z Ning - Medical Image Analysis, 2025 - Elsevier
Automatically labeling and segmenting vertebrae in 3D CT images compose a complex
multi-task problem. Current methods progressively conduct vertebra labeling and semantic …

Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query Embedding

H Guo, J Zhang, K Yan, L Lu… - IEEE Journal of Biomedical …, 2024 - ieeexplore.ieee.org
Automatic parsing of human anatomies at the instance-level from 3D computed tomography
(CT) is a prerequisite step for many clinical applications. The presence of pathologies …

SLoRD: Structural Low-Rank Descriptors for Shape Consistency in Vertebrae Segmentation

X You, Y Lou, M Zhang, J Yang, N Navab… - arxiv preprint arxiv …, 2024 - arxiv.org
Automatic and precise multi-class vertebrae segmentation from CT images is crucial for
various clinical applications. However, due to a lack of explicit consistency constraints …

VertFound: Synergizing Semantic and Spatial Understanding for Fine-Grained Vertebrae Classification via Foundation Models

Y Wu, J Tang, Z Yao, M Li, Y Hong, D Yu, Z Gao… - … Conference on Medical …, 2024 - Springer
Achieving automated vertebrae classification in spine images is a crucial yet challenging
task due to the repetitive nature of adjacent vertebrae and limited fields of view (FoV) …

Explainable Vertebral Fracture Analysis with Uncertainty Estimation Using Differentiable Rule-Based Classification

V Wåhlstrand Skärström, L Johansson, J Alvén… - … Conference on Medical …, 2024 - Springer
We present a novel method for explainable vertebral fracture assessment (XVFA) in low-
dose radiographs using deep neural networks, incorporating vertebra detection and …

Swin-X2S: Reconstructing 3D Shape from 2D Biplanar X-ray with Swin Transformers

K Liu, Z Ying, J **, D Li, P Huang, W Wu… - arxiv preprint arxiv …, 2025 - arxiv.org
The conversion from 2D X-ray to 3D shape holds significant potential for improving
diagnostic efficiency and safety. However, existing reconstruction methods often rely on …

Explainable vertebral fracture analysis with uncertainty estimation using differentiable rule-based classification

VW Skärström, L Johansson, J Alvén… - arxiv preprint arxiv …, 2024 - arxiv.org
We present a novel method for explainable vertebral fracture assessment (XVFA) in low-
dose radiographs using deep neural networks, incorporating vertebra detection and …