DTG: Dual transformers-based generative adversarial networks for retinal 2D/3D OCT image classification [0.03%]
基于双变换器的生成对抗网络用于视网膜2D/3D OCT图像分类
Badr Ait Hammou,Renaud Duval,Marie-Carole Boucher et al.
Badr Ait Hammou et al.
The automated identification of retinal disorders is one of the most popular real-world computer vision applications related to ophthalmology. It has several advantages and can help ophthalmologists identify diseases more accurately. Techni...
UDV-Net: A hybrid CNN and transformer vein segmentation network with vascular prior and spatial awareness [0.03%]
一种基于血管先验和空间感知的混合CNN与Transformer静脉分割网络（UDV-Net）
Bowei Shen,Xiaoquan Huang,Yuli Li et al.
Bowei Shen et al.
CNNs handling multi-scale variations and Transformers modeling long-range dependencies are crucial for vascular segmentation. The fusion of these two models effectively combines the multi-scale local features extracted by CNNs with the glob...
DVAP-Reg: Dual-view anatomical prior-driven cross-dimensional registration for spinal surgery navigation [0.03%]
基于双视图解剖先验的脊柱手术导航中的跨维度配准方法(DVAP-Reg)
Zhengyang Wu,Wenjie Zheng,Yingjie Hao et al.
Zhengyang Wu et al.
2D-3D cross-dimensional registration serves as a critical technology in spinal surgery navigation, with profound implications for enhancing surgical precision, reducing radiation exposure and mitigating surgical risks. Its core objective is...
STCMT-Net: A spatiotemporal consistency motion transfer network for enhancing cardiac motion estimation [0.03%]
具有时空一致性的运动传输网络在心脏运动估算中的应用
Xiaoya Qiao,Jiwei Yu,Hanzhong Wang et al.
Xiaoya Qiao et al.
Cardiac motion estimation is critical for assessing cardiac function and understanding cardiac mechanics. However, the complex and subject-specific characteristics of cardiac motion pose substantial challenges for modeling the spatiotempora...
FDA-Recon: Feature and data alignment reconstruction for sparse-view CBCT [0.03%]
基于特征和数据对齐的稀疏视图锥束CT重建方法(fda-recon)
Yikun Zhang,Yao Wang,Xian Wu et al.
Yikun Zhang et al.
Cone-beam computed tomography (CBCT) enables real-time three-dimensional imaging for patients, which is of great significance in improving the precision of radiotherapy and interventional procedures. Sparse-view CBCT, which can relax the re...
Multi-cancer framework with cancer-aware attention and adversarial mutual-information minimization for whole slide image classification [0.03%]
一种基于癌症感知注意和对抗最小化互信息的多癌种全切片图像分类框架
Sharon Peled,Yosef E Maruvka,Moti Freiman
Sharon Peled
Whole Slide Images (WSIs) are crucial in modern pathology, offering high-resolution data for accurate diagnosis, treatment planning, and research. Deep learning methods have recently been proposed to harness this data by extracting and inte...
Spatial-frequency dual-constrained Mamba diffusion model for cross-modal generation from CFP to FFA [0.03%]
基于空间频率双约束的马巴扩散模型CFP到FFA的跨模态生成
Qing Liu,Hongqing Zhu,Tianwei Qian et al.
Qing Liu et al.
Fundus Fluorescein Angiography (FFA) is a critical imaging technique for visualizing retinal vascular dynamics and diagnosing various retinal pathologies. However, its reliance on intravenous fluorescein dye may pose risks of nausea, allerg...
Unsupervised anomaly detection in brain MRI via disentangled anatomy learning [0.03%]
基于解构解剖学学习的脑MRI无监督异常检测
Tao Yang,Xiuying Wang,Hao Liu et al.
Tao Yang et al.
Detection of various lesions in brain MRI is clinically critical, but challenging due to the diversity of lesions and variability in imaging conditions. Current unsupervised learning methods detect anomalies mainly through reconstructing ab...
Segmentation-enhanced multi-scale deep hashing for chest X-ray image retrieval [0.03%]
一种改进的多尺度深度哈希算法用于胸部X光图像检索
Linmin Wang,Qianqian Wang,Xiaochuan Wang et al.
Linmin Wang et al.
Chest X-ray (CXR) images play a crucial role in diagnosing COVID-19 by facilitating the rapid identification of lung damage. Recently, deep hashing technology has enhanced our capabilities for retrieving large CXR image databases, providing...
DFuse-Net: Disentangled feature fusion with uncertainty-aware learning for reliable multi-modal brain tumor segmentation [0.03%]
基于不确定性感知学习的解缠多模态脑肿瘤分割特征融合网络
Tongxue Zhou,Zheng Wang,Su Ruan et al.
Tongxue Zhou et al.
Accurate brain tumor segmentation from multi-modal MRI is critical for clinical diagnosis and treatment planning. However, effectively exploiting the complementary information across different modalities remains challenging due to modality-...