Dual-Phase Computed Tomography-Based Deep Learning Architecture for Three-Year Survival Prediction in Hepatocellular Carcinoma [0.03%]
基于双相CT的深度学习架构用于肝细胞癌三年生存率预测
You-Wei Wang,Tse-Chun Huang,Shang-Yu Chiang et al.
You-Wei Wang et al.
Hepatocellular carcinoma (HCC) is a major global health burden, ranking as the sixth most common cancer and the third leading cause of cancer-related mortality. Computed tomography (CT) is widely used for HCC evaluation because of the high ...
Enhancing Anatomy Learning Through Enhanced 3D Visualization: A Study on Student Perception and Engagement in Museum-Based Education [0.03%]
增强三维可视化以提升解剖学学习：一项关于学生在基于博物馆的教育中的感知和参与度的研究
Bali Sharma,Amani Alhazmi,Nazim Nasir et al.
Bali Sharma et al.
Effective anatomy education is essential for medical training. While traditional anatomy instruction provides essential foundational knowledge, its effectiveness depends on the instructional format, level of interaction, and availability of...
Transfer learning for Multi-institutional Classification of Intussusception and Splenomegaly in Pediatric Abdominal Radiographs [0.03%]
基于儿童腹部X光片的肠套叠和脾肿大多机构分类中的迁移学习
Minsoo Shin,Sungwon Ham,Yoon Lee et al.
Minsoo Shin et al.
To address diagnostic delays in pediatric abdominal emergencies, this study aimed to develop and validate multi-institutional deep learning models for detecting intussusception and splenomegaly on abdominal radiographs, thereby evaluating t...
Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis [0.03%]
基于多模态医学影像分析的深度学习框架在胰腺癌早期检测中的应用研究
Dennis Slobodzian,Amir Kordijazi
Dennis Slobodzian
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal forms of cancer, with a five-year survival rate below 10% primarily due to late detection [1]. This research develops and validates a deep learning framework for early P...
CBAM-Xception: An Attention-Guided Framework for Skin Cancer Classification [0.03%]
基于CBAM-Xception的皮肤癌分类注意力引导框架
Faysal Ahmmed,Ajmy Alaly,Samanta Mehnaj et al.
Faysal Ahmmed et al.
Skin cancer is a potentially fatal disease that requires early and accurate diagnosis to improve patient outcomes. Deep learning has shown promise in automating skin lesion classification; however, many existing models suffer from limited i...
Impact of CT Acquisition Parameters on Deep Learning of Aortic Segmentation Performance: Systematic Review [0.03%]
CT采集参数对主动脉分割深度学习性能影响的系统评价
Erika Spinella,Marco Magliocco,Curzio Basso et al.
Erika Spinella et al.
Automatic segmentation of computed tomography (CT) images is fundamental for quantitative anatomical analysis in a wide range of clinical applications. Despite remarkable advances in artificial intelligence (AI), CT acquisition parameters c...
An Intensity-Based Cropping Approach for Fast, Interpretable, and Robust Localization of the Knee Joint in Radiographs [0.03%]
一种基于强度的裁剪方法，用于放射图中膝关节快速、可解释和鲁棒定位
Mohammadreza Chavoshi,Hari Trivedi,Janice Newsome et al.
Mohammadreza Chavoshi et al.
Effective image preprocessing is critical for ensuring the robustness and generalizability of downstream models by preventing shortcut learning on spurious features. Knee joint localization is essential for reliable pathology assessment by ...
Segmentation and 3D Visualization of Spinal Motion Segments from MSCT Images Using a 3D U‑Net Framework [0.03%]
基于3D U-Net框架的脊柱运动节段分割及MSCT图像三维可视化研究
Antor Mahamudul Hashan,Khlebnikov Nikolai Alexandrovich,Denis Protasov
Antor Mahamudul Hashan
Segmentation of spinal motion segments from multi‑slice computed tomography (MSCT) images is essential for clinical evaluation and pre‑operative planning. This study presents a fully automated framework that combines a three‑dimensional ...
H2M-UNet: Hierarchical Memory Mamba-Driven UNet Collaborative Optimization Based on Long-Range Forgetting Mitigation and Fine-Grained Feature Capture [0.03%]
基于长程遗忘缓解和细粒度特征捕获的层次化记忆拟步蛇驱动UNET协同优化方法
Guodong Zhang,Xiaoyu Fang,Ronghui Ju et al.
Guodong Zhang et al.
In medical image segmentation, conventional state-space-model-based Mamba networks suffer from long-range forgetting due to locally dependent scanning mechanisms, which compromises prediction consistency and segmentation accuracy when proce...
Differential Attention Feature Aggregator (DAFE) for Advanced Melanoma Detection [0.03%]
用于高级黑色素瘤检测的差异注意特征聚合器(DAFE)
YuJie Chen,ChunLin Wang,Jianzhong Peng et al.
YuJie Chen et al.
Melanoma is a highly aggressive form of skin cancer with a significant mortality rate. Over the past two decades, its incidence has been on the rise and is projected to increase further in the future. Early treatment has a higher survival r...