Robust Bayesian brain extraction by integrating structural subspace-based spatial prior into deep neural networks [0.03%]
基于结构子空间的鲁棒贝叶斯脑提取方法
Yunpeng Zhang,Huixiang Zhuang,Yue Guan et al.
Yunpeng Zhang et al.
Accurate and robust brain extraction, or skull stripping, is essential for studying brain development, aging, and neurological disorders. However, brain images exhibit substantial data heterogeneity due to differences in contrast and geomet...
Physics-informed neural networks for denoising high b-value diffusion-weighted images [0.03%]
基于物理的神经网络去噪高b值弥散加权影像
Qiaoling Lin,Fan Yang,Yang Yan et al.
Qiaoling Lin et al.
Diffusion-weighted imaging (DWI) is widely applied in tumor diagnosis by measuring the diffusion of water molecules. To increase the sensitivity to tumor identification, faithful high b-value DWI images are expected by setting a stronger st...
MedBLIP: A multimodal method of medical question-answering based on fine-tuning large language model [0.03%]
基于大型语言模型微调的医学问答多模态方法MedBLIP
Lejun Gong,Jiaming Yang,Shengyuan Han et al.
Lejun Gong et al.
Medical visual question answering is crucial for effectively interpreting medical images containing clinically relevant information. This study proposes a method called MedBLIP (Medical Treatment Bootstrapping Language-Image Pretraining) to...
OSAM-NET: A multi-feature fusion model for measuring fetal head flexion during labor with transformer multi-head self-attention [0.03%]
基于Transformer多头自注意力的胎儿头部屈曲度量化模型
Shijie Zhang,Shaozheng He,Jingjing Wu et al.
Shijie Zhang et al.
Fetal head flexion is essential during labor. The current assessment presents technical challenges for unskilled ultrasound operators. Therefore, the study aimed to propose an occiput-spine angle measurement network (OSAM-NET) to improve th...
A segmentation network based on CNNs for identifying laryngeal structures in video laryngoscope images [0.03%]
一种基于CNN的视频喉镜图像下喉部结构识别分割网络
Jinjing Wu,Wenhui Guo,Zhanheng Chen et al.
Jinjing Wu et al.
Video laryngoscopes have become increasingly vital in tracheal intubation, providing clear imaging that significantly improves success rates, especially for less experienced clinicians. However, accurate recognition of laryngeal structures ...
Unpaired multi-modal training and single-modal testing for detecting signs of endometriosis [0.03%]
用于检测子宫内膜异位症征兆的非配对多模态训练和单模态测试
Yuan Zhang,Hu Wang,David Butler et al.
Yuan Zhang et al.
Endometriosis is a serious multifocal condition that can involve various pelvic structures, with Pouch of Douglas (POD) obliteration being a significant clinical indicator for diagnosis. To circumvent the need for invasive diagnostic proced...
Evaluation of uncertainty estimation methods in medical image segmentation: Exploring the usage of uncertainty in clinical deployment [0.03%]
医学图像分割中不确定性估计方法的评估：探索不确定性在临床应用中的使用价值
Shiman Li,Mingzhi Yuan,Xiaokun Dai et al.
Shiman Li et al.
Uncertainty estimation methods are essential for the application of artificial intelligence (AI) models in medical image segmentation, particularly in addressing reliability and feasibility challenges in clinical deployment. Despite their s...
Deep learning model for malignancy prediction of TI-RADS 4 thyroid nodules with high-risk characteristics using multimodal ultrasound: A multicentre study [0.03%]
基于多模态超声的TI-RADS 4类甲状腺结节恶性风险特征的深度学习模型预测：一项多中心研究
Xuan Chu,Tengfei Wang,Meiwen Chen et al.
Xuan Chu et al.
The automatic screening of thyroid nodules using computer-aided diagnosis holds great promise in reducing missed and misdiagnosed cases in clinical practice. However, most current research focuses on single-modal images and does not fully l...
MFFUNet: A hybrid model with cross-attention-guided multi-feature fusion for automated segmentation of organs at risk in cervical cancer brachytherapy [0.03%]
基于交叉注意力的多特征融合模型MFFUNet在宫颈癌后装放疗危及器官自动勾画中的应用
Yin Gu,Huimin Guo,Jiahao Zhang et al.
Yin Gu et al.
Brachytherapy is a common treatment option for cervical cancer. An important step involved in brachytherapy is the delineation of organs at risk (OARs) based on computed tomography (CT) images. Automating OARs segmentation in brachytherapy ...
PDS-UKAN: Subdivision hopping connected to the U-KAN network for medical image segmentation [0.03%]
PDS-UKAN：通过U-KAN网络进行医学图像分割的子区域跳转模型
Liwei Deng,Wenbo Wang,Songyu Chen et al.
Liwei Deng et al.
Accurate and efficient segmentation of medical images plays a vital role in clinical tasks, such as diagnostic procedures and planning treatments. Traditional U-shaped encoder-decoder architectures, built on convolutional and transformer-ba...