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...
Dingchang Wu,Yinghui Wang,Haomiao Ma et al.
Dingchang Wu et al.
The traditional feature-extraction method of oriented FAST and rotated BRIEF (ORB) detects image features based on a fixed threshold; however, ORB descriptors do not distinguish features well in capsule endoscopy images. Therefore, a new fe...
Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma [0.03%]
基于影像组学的磁共振及动态增强磁共振综合集成分析在鼻咽癌预后预测中的应用研究
Hailin Li,Weiyuan Huang,Siwen Wang et al.
Hailin Li et al.
Although prognostic prediction of nasopharyngeal carcinoma (NPC) remains a pivotal research area, the role of dynamic contrast-enhanced magnetic resonance (DCE-MR) has been less explored. This study aimed to investigate the role of DCR-MR i...
Local imperceptible adversarial attacks against human pose estimation networks [0.03%]
针对姿态估计网络的局部不可察觉对抗攻击
Fuchang Liu,Shen Zhang,Hao Wang et al.
Fuchang Liu et al.
Deep neural networks are vulnerable to attacks from adversarial inputs. Corresponding attack research on human pose estimation (HPE), particularly for body joint detection, has been largely unexplored. Transferring classification-based atta...