[Automatic epilepsy detection with an attention-based multiscale residual network] [0.03%]
基于注意的多尺度残差网络的自动癫痫检测
Xingqi Wang,Ming&#x;ai Li
Xingqi Wang
The deep learning-based automatic detection of epilepsy electroencephalogram (EEG), which can avoid the artificial influence, has attracted much attention, and its effectiveness mainly depends on the deep neural network model. In this paper...
[Identifying spatial domains from spatial transcriptome by graph attention network] [0.03%]
基于图注意力网络的Spatial Transcriptomics数据空间域识别方法
Hanwen Wu,Jie Gao
Hanwen Wu
Due to the high dimensionality and complexity of the data, the analysis of spatial transcriptome data has been a challenging problem. Meanwhile, cluster analysis is the core issue of the analysis of spatial transcriptome data. In this artic...
[Breast cancer lesion segmentation based on co-learning feature fusion and Transformer] [0.03%]
基于协同学习特征融合和Transformer的乳腺癌病灶分割方法研究
Yuesong Zhai,Zhili Chen,Dan Shao
Yuesong Zhai
The PET/CT imaging technology combining positron emission tomography (PET) and computed tomography (CT) is the most advanced imaging examination method currently, and is mainly used for tumor screening, differential diagnosis of benign and ...
[Automatic detection method of intracranial aneurysms on maximum intensity projection images based on SE-CaraNet] [0.03%]
基于SE-CaraNet的颅内瘤检测方法研究
Peirui Bai,Xuefeng Song,Qingyi Liu et al.
Peirui Bai et al.
Conventional maximum intensity projection (MIP) images tend to ignore some morphological features in the detection of intracranial aneurysms, resulting in missed detection and misdetection. To solve this problem, a new method for intracrani...
[Medical image segmentation data augmentation method based on channel weight and data-efficient features] [0.03%]
基于通道权重和数据高效特征的医学图像分割数据增强方法
Xing Wu,Chenjie Tao,Zhi Li et al.
Xing Wu et al.
In computer-aided medical diagnosis, obtaining labeled medical image data is expensive, while there is a high demand for model interpretability. However, most deep learning models currently require a large amount of data and lack interpreta...
[Brain magnetic resonance image registration based on parallel lightweight convolution and multi-scale fusion] [0.03%]
基于并行轻量级卷积和多尺度融合的脑磁共振图像配准方法研究
Yu Shen,Yuan Yan,Jing Song et al.
Yu Shen et al.
Medical image registration plays an important role in medical diagnosis and treatment planning. However, the current registration methods based on deep learning still face some challenges, such as insufficient ability to extract global info...
[Prediction of recurrence-free survival in lung adenocarcinoma based on self-supervised pre-training and multi-task learning] [0.03%]
基于自监督预训练和多任务学习的肺腺癌无复发生存预测模型研究
Lunyu Hu,Wei Xia,Qiong Li et al.
Lunyu Hu et al.
Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarcinoma, and using CT images to predict the recurrence-free survival (RFS) of lung adenocarcinoma patients post-surgery is of paramount importa...
[Research progress of methylcellulose-based thermosensitive hydrogels applied in biomedical field] [0.03%]
甲基纤维素基温敏水凝胶在生物医学领域中的研究进展
Junting Xiong,Longfei Feng,Baolin Liu et al.
Junting Xiong et al.
Methylcellulose is a semi-flexible cellulose ether derivative, whose hydrogels are thermosensitive and reversible, with good biocompatibility and adjustable function, and its application has attracted much attention in the biomedical field....
Xuhong He,Chaiqiong Guo,Xuanyu Liu et al.
Xuhong He et al.
In recent years, bone implant materials such as titanium and titanium alloys have been widely used in the biomedical field due to their excellent mechanical properties and good biocompatibility. However, in clinical practice, bacterial adhe...
[Developments of ex vivo cardiac electrical mapping and intelligent labeling of atrial fibrillation substrates] [0.03%]
离体心脏电标测及心房颤动基质的智能化标测技术进展
Yi Chang,Ming Dong,Bin Wang et al.
Yi Chang et al.
Cardiac three-dimensional electrophysiological labeling technology is the prerequisite and foundation of atrial fibrillation (AF) ablation surgery, and invasive labeling is the current clinical method, but there are many shortcomings such a...