Multi-needle Localization for Pelvic Seed Implant Brachytherapy based on Tip-handle Detection and Matching [0.03%]
基于针尖-柄检测与匹配的盆腔种子植入定位方法研究
Zhuo Xiao,Fugen Zhou,Jingjing Wang et al.
Zhuo Xiao et al.
Accurate multi-needle localization in intraoperative CT images is crucial for optimizing seed placement in pelvic seed implant brachytherapy. However, this task is challenging due to poor image contrast and needle adhesion. This paper prese...
A Multimodal Learning Framework for Detecting Systemic Hypertension in Sleep Apnea Patients Using ECG and PPG Signals [0.03%]
一种用于检测睡眠呼吸暂停患者中全身高血压的多模态学习框架使用ECG和PPG信号
Hisham ElMoaqet,Rami Janini,Mutaz Ryalat et al.
Hisham ElMoaqet et al.
Systemic hypertension (HTN) is a major cardiovascular comorbidity in patients with obstructive sleep apnea (OSA), yet these conditions are often diagnosed and managed independently, limiting integrated cardiovascular risk assessment. There ...
Progressive Orthogonal Multimodal Similarity Learning for Metabolite-Disease Association Prediction [0.03%]
一种渐进式正交多模态相似度学习的代谢物-疾病关联预测方法
Qiao Ning,Yanpeng Liu,Yuanjie Li et al.
Qiao Ning et al.
The identification of potential associations between metabolites and diseases is crucial for understanding the onset and progression of diseases. Although numerous methods have been developed to predict metabolite-disease associations (MDAs...
Long-Term, Patient-Specific Seizure Prediction using Absolute Mean Instantaneous Frequency Difference (AMIFD) and Seizure Clustering [0.03%]
基于绝对平均瞬时频率差（AMIFD）和癫痫发作聚类的长期个体化癫痫发作预测方法
Sai Sanjay Balaji,Zisheng Zhang,Zhiyi Sha et al.
Sai Sanjay Balaji et al.
Long-term seizure prediction in epileptic individuals is challenging, mainly due to signal non-stationarity and seizure type variability. This research presents a patient-specific prediction pipeline for intracranial electroencephalography ...
Concept-Aware Adaptive Multimodal Fusion With Knowledge Distillation for Medical Image Diagnosis [0.03%]
基于知识蒸馏的医学图像诊断的概念感知自适应多模态融合方法
Jing Li,Xiaorou Zheng,Yalin Zheng et al.
Jing Li et al.
Multimodal medical image has emerged as a powerful tool for improving diagnostic accuracy by leveraging complementary information from diverse imaging modalities. However, existing methods often fail to account for disease-specific modality...
Enhancing Lesion Segmentation via Medical Image-Mask Pair Synthesis using Phenotype-Conditioned Diffusion Models [0.03%]
基于表型条件的扩散模型的医学图像-掩码对合成以增强病变分割
Fei Lyu,Jingwen Xu,Ye Zhu et al.
Fei Lyu et al.
Accurate lesion segmentation in medical images is critical for early diagnosis and treatment planning, yet it remains challenging because training robust lesion segmentation models suffers from the data scarcity and sample imbalance issues....
A Foundation Model for Wearable Movement Data in Mental Health Research [0.03%]
精神健康研究中的可穿戴设备运动数据基础模型
Franklin Y Ruan,Aiwei Zhang,Jenny Y Oh et al.
Franklin Y Ruan et al.
Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, reflecting fine-grained temporal behavioral trends. Despite its promise, the development of foundat...
SPARNet: A Framework for Airway Invasion Tracking from Fluoroscopic Videos of Dysphagia Patients [0.03%]
基于吞咽困难患者荧光视频的气管侵入跟踪框架
Sanjeevi G,Uma Gopalakrishnan,Rahul Krishnan Pathinarupothi et al.
Sanjeevi G et al.
The videofluoroscopic swallowing study (VFSS) is the clinical gold standard for evaluating dysphagia and detecting airway invasion. However, manual interpretation is time-consuming, subjective, and prone to rater variability due to the rapi...
Domain-agnostic Unsupervised Domain Adaptation Segmentation from 3D Carotid Artery Ultrasound Image [0.03%]
一种来自3D颈动脉超声图像的领域无关无监督领域适应分割方法
Zheng Yue,Liping Liu,J David Spence et al.
Zheng Yue et al.
Automatic segmentation of the vessel wall in three-dimensional (3D) carotid artery (CA) ultrasound (US) images can significantly advance the development of cardiovascular disease risk prediction and therapy assessments. Unsupervised domain ...
GTAFL: Addressing Test-Agnostic Long-Tailed Federated Learning in Medical Image [0.03%]
基于医学图像的测试无关的长尾联邦学习问题及其解决方案GTAFL
Guangyu Chen,Jingyun Zeng,Hui Jiang
Guangyu Chen
In healthcare, protecting patient privacy is crucial due to the sensitivity of medical data and its extensive accessibility. Federated Learning (FL) offers a decentralized and privacy-preserving training paradigm, making it an ideal solutio...