Phase-lag Based MPS/MPI Dual-mode Precise in vivo Temperature Imaging Technique [0.03%]
基于相位滞后的体内精确温度成像的MPS/MPI双模技术
Siao Lei,Wenxuan Zou,Yanjun Liu et al.
Siao Lei et al.
Magnetic Particle Imaging (MPI) enables noninvasive temperature imaging without depth limitations. However, due to the lack of effective calibration strategies that can simultaneously address issues such as calibration infeasibility and env...
Computed Quantitative Planar Imaging for Targeted Alpha Therapy: Model-Based Sparse Reconstruction Validated with a Novel 225Ac Epoxy Phantom [0.03%]
基于模型的稀疏重建进行靶向α治疗的计算定量平面成像：使用新型225Ac环氧树脂模体验证
C Ross Schmidtlein,Jin Ren,Andrzej Krol et al.
C Ross Schmidtlein et al.
Targeted Alpha Therapy (TAT), using alpha-emitting radionuclides (AER) such as 225Ac, shows promise for the treatment of advanced and refractory cancers. Currently, TAT is prescribed on the basis of activity (e.g., MBq, kBq/kg), with no acc...
Disentangled Multi-modal Learning of Histology and Transcriptomics for Cancer Characterization [0.03%]
基于组织学和转录组的解缠绕多模态学习的癌症表征
Yupei Zhang,Xiaofei Wang,Anran Liu et al.
Yupei Zhang et al.
Histopathology remains the gold standard for cancer diagnosis and prognosis. With the advent of transcriptome profiling, multi-modal learning combining transcriptomics with histology offers more comprehensive information. However, existing ...
Preoperative Prediction of Esophageal Cancer Survival in CT via Tumor and Lymph Node Context and Geometry Modeling [0.03%]
基于肿瘤和淋巴结解剖位置及形态的食管癌预后判断模型
Xuan Gong,Jiaqi Li,Yirui Wang et al.
Xuan Gong et al.
Esophageal cancer is one of the most lethal cancers, with 5-year survival rate of only 20%. Patient outcomes can vary significantly even though they are at the same cancer stage and receive similar treatments. Accurate prognostic prediction...
Tomographic Foundation Model-FORCE: Flow-Oriented Reconstruction Conditioning Engine [0.03%]
层析基础模型-FORCE：以流动为导向的重构条件引擎
Wenjun Xia,Chuang Niu,Ge Wang
Wenjun Xia
Computed tomography (CT) is a major medical imaging modality. Clinical CT scenarios, such as low-dose screening, sparse-view scanning, and metal implants, often lead to severe noise and artifacts in reconstructed images, requiring improved ...
Dynamic Registration-Based Photoacoustic Endoscopic Temperature Imaging for Precision Interventional Thermal Therapy and Monitoring [0.03%]
基于动态注册的体内光声温度成像技术引导精准介入热疗及监测
Dongjian Wu,Kaicheng Yu,Haokun Zhang et al.
Dongjian Wu et al.
Atherosclerosis is a major cause of cardiovascular disease. Photothermal ablation provides a minimally invasive therapeutic approach but remains constrained by the lack of reliable temperature monitoring. Conventional thermometry provides o...
Scan-invariant Mamba with Differentiated Sequence Contrastive Learning in Computational Pathology [0.03%]
基于差异化序列对比学习的扫描不变马米巴方法在计算病理学中的应用
Sheng Huang,Xin Zhang,Xiang Zhu et al.
Sheng Huang et al.
Multiple instance learning (MIL) is a commonly used paradigm for histopathological analysis due to the ultra-high resolution and coarse-grained labels of Whole Slide Images (WSIs). Recent studies apply Mamba architecture to WSI classificati...
MARVEL: Motion-Aware Reconstruction Via Embedded Learning of Motion Prior for Time-Resolved Cardiac CT [0.03%]
基于运动先验嵌入学习的时序 cardiac ct 的运动感知重建方法 (marvel)
Ziheng Deng,Xiaowei Liu,Weikang Zhang et al.
Ziheng Deng et al.
Cardiac CT provides comprehensive structural and functional heart imaging, but motion artifacts remain a fundamental challenge. Although modern scanners have improved temporal resolution through hardware advancements and electrocardiogram-g...
Decouple, Reorganize, and Fuse: A Multimodal Framework for Cancer Survival Prediction [0.03%]
解耦、重组与融合：一种癌症生存预测的多模态框架
Huayi Wang,Haochao Ying,Yuyang Xu et al.
Huayi Wang et al.
Cancer survival analysis commonly integrates information across diverse medical modalities to make survival-time predictions. Existing methods primarily focus on extracting different decoupled features of modalities and performing fusion op...
QuPaS: SAM-based Semi-supervised Histopathological Image Segmentation with Quantum Force Field Finetuning and Adversarial Estimation [0.03%]
基于SAM的半监督组织病理图像分割方法：量子力场微调与对抗估计
Siyang Feng,Xipeng Pan,Weidong Zhang et al.
Siyang Feng et al.
Semi-supervised segmentation (S3) is one of the preferred choices for histopathological image segmentation tasks, while how to improve model's learning capability for unlabeled data remains a key challenge in S3. The remarkable feature extr...