Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification [0.03%]
一种典型的实例依赖的对抗标签噪声的框架：模拟和对抗内镜下息肉分类的真实世界中的噪声标签的一种新框架
Yun Gao,Junhu Fu,Yuanyuan Wang et al.
Yun Gao et al.
Learning with noisy labels aims to train neural networks with noisy labels. Current models handle instance-independent label noise (IIN) well; however, they fall short with real-world noise. In medical image classification, atypical samples...
Dual modality prompt learning for visual question-grounded answering in robotic surgery [0.03%]
机器人手术中用于视觉问答的双模态提示学习方法
Yue Zhang,Wanshu Fan,Peixi Peng et al.
Yue Zhang et al.
With recent advancements in robotic surgery, notable strides have been made in visual question answering (VQA). Existing VQA systems typically generate textual answers to questions but fail to indicate the location of the relevant content w...
Automated analysis of pectoralis major thickness in pec-fly exercises: evolving from manual measurement to deep learning techniques [0.03%]
胸大肌厚度在飞鸟运动中的自动化分析：从手动测量到深度学习技术的发展
Shangyu Cai,Yongsheng Lin,Haoxin Chen et al.
Shangyu Cai et al.
This study addresses a limitation of prior research on pectoralis major (PMaj) thickness changes during the pectoralis fly exercise using a wearable ultrasound imaging setup. Although previous studies used manual measurement and subjective ...
Zhenxing Xu,Aizeng Wang,Fei Hou et al.
Zhenxing Xu et al.
This study proposes an image-based three-dimensional (3D) vector reconstruction of industrial parts that can generate non-uniform rational B-splines (NURBS) surfaces with high fidelity and flexibility. The contributions of this study includ...
PlaqueNet: deep learning enabled coronary artery plaque segmentation from coronary computed tomography angiography [0.03%]
基于冠状动脉CT血管成像的动脉粥样斑块深度学习分割网络（PlaqueNet）
Linyuan Wang,Xiaofeng Zhang,Congyu Tian et al.
Linyuan Wang et al.
Cardiovascular disease, primarily caused by atherosclerotic plaque formation, is a significant health concern. The early detection of these plaques is crucial for targeted therapies and reducing the risk of cardiovascular diseases. This stu...
Yuxuan Liang,Chuang Niu,Pingkun Yan et al.
Yuxuan Liang et al.
Flipover, an enhanced dropout technique, is introduced to improve the robustness of artificial neural networks. In contrast to dropout, which involves randomly removing certain neurons and their connections, flipover randomly selects neuron...
Correction: Multi-task approach based on combined CNN-transformer for efficient segmentation and classification of breast tumors in ultrasound images [0.03%]
修正：基于组合卷积神经网络-变压器的多任务方法用于超声图像中乳腺肿瘤的有效分割和分类
Jaouad Tagnamas,Hiba Ramadan,Ali Yahyaouy et al.
Jaouad Tagnamas et al.
Convolutional neural network based data interpretable framework for Alzheimer's treatment planning [0.03%]
基于卷积神经网络的阿尔茨海默病治疗计划的数据可解释框架
Sazia Parvin,Sonia Farhana Nimmy,Md Sarwar Kamal
Sazia Parvin
Alzheimer's disease (AD) is a neurological disorder that predominantly affects the brain. In the coming years, it is expected to spread rapidly, with limited progress in diagnostic techniques. Various machine learning (ML) and artificial in...
Multi-task approach based on combined CNN-transformer for efficient segmentation and classification of breast tumors in ultrasound images [0.03%]
结合CNN-Transformer的多任务方法在超声图像中对乳腺肿瘤进行有效分割和分类
Jaouad Tagnamas,Hiba Ramadan,Ali Yahyaouy et al.
Jaouad Tagnamas et al.
Accurate segmentation of breast ultrasound (BUS) images is crucial for early diagnosis and treatment of breast cancer. Further, the task of segmenting lesions in BUS images continues to pose significant challenges due to the limitations of ...
CT-based radiomics: predicting early outcomes after percutaneous transluminal renal angioplasty in patients with severe atherosclerotic renal artery stenosis [0.03%]
基于CT的放射组学：预测严重动脉粥样硬化性肾动脉狭窄患者经皮腔内肾成形术后早期结局
Jia Fu,Mengjie Fang,Zhiyong Lin et al.
Jia Fu et al.
This study aimed to comprehensively evaluate non-contrast computed tomography (CT)-based radiomics for predicting early outcomes in patients with severe atherosclerotic renal artery stenosis (ARAS) after percutaneous transluminal renal angi...