Sex-Related Performance Disparities in Convolutional Neural Networks for Imaging-Based Assessment of Coronary Atherosclerosis and Ischemic Heart Disease: A Systematic Review [0.03%]
基于影像的冠状动脉动脉粥样硬化和缺血性心脏病评估中卷积神经网络的性别差异性能：一项系统综述
Aya Mudrik,Ayala Dodge,Alon Moore Galindo et al.
Aya Mudrik et al.
Sex-related disparities persist in the diagnosis and management of ischemic heart disease (IHD), raising concern that convolutional neural networks (CNNs) used in coronary imaging may perpetuate these inequities. This systematic review eval...
Learning Geometric Information Propagation for Semi-supervised 3D Medical Image Segmentation [0.03%]
几何信息传播学习在半监督的医学图像三维分割中的应用
Lianyuan Yu,Xiuzhen Guo,Ji Shi et al.
Lianyuan Yu et al.
Semi-supervised learning enhances medical image segmentation by leveraging unlabeled data, reducing reliance on extensive labeled datasets. We observe that medical images usually exhibit consistent anatomical structures defined by geometric...
Rethinking Architectural Complexity in Deep Vision Models for Histopathological Image Classification [0.03%]
深度视觉模型在组织病理图像分类中的架构复杂性再思考
Qaiser Abbas,Muhammad Irzam Liaqat,Sabahat Qayum et al.
Qaiser Abbas et al.
Recent advances in deep learning for histopathological image analysis have led to increasingly complex architectures that require substantial computational resources and large datasets. While these models achieve strong performance, they of...
LDM-Echo: A Latent Diffusion Model for Echocardiographic Image Denoising with Clinical Evaluation [0.03%]
基于临床评估的心脏超声图像去噪的潜在扩散模型(LDM-Echo)
Samira Jaballah,Tarak Ben Said,Imen Baklouti et al.
Samira Jaballah et al.
Speckle noise in echocardiographic imaging degrades contrast, obscures anatomical structures, and compromises quantitative measurements. Effective suppression of this noise is critical, yet traditional denoising methods often cause structur...
pix2pixHDv2: Efficient Panoramic Dental Image Synthesis with Minimal Artifacts and Computational Overhead [0.03%]
带极少伪影和计算开销的高效全景牙科图像合成Pix2PixHDv2
Merter Hami Karacan,Sait Can Yucebas
Merter Hami Karacan
Although recent image-generation studies have achieved promising results, they still present challenges in terms of computational cost and training/inference time that need to be addressed. Conditional generative adversarial networks (mask-...
Bidirectional Weighted Cross-Entropy for Imbalanced Pressure Injury Classification [0.03%]
不平衡压力性损伤的双向加权交叉熵分类方法
Jong Chan Yeom,Eun Jin Han,Ah Young Kim et al.
Jong Chan Yeom et al.
Accurate classification of pressure injuries from clinical images remains challenging because clinical datasets are often small and class-imbalanced. We propose bidirectional weighted cross-entropy (BWCE), a conditional prediction-dependent...
Explainable Deep Learning for Automated Classification of Skeletal and Tumor Pathologies in 3D Volumetric Medical Imaging [0.03%]
基于解释性深度学习的三维体数据医学图像骨骼和肿瘤分类模型自动化研究
Ahmad Almadhor,Stephen Ojo,Thomas I Nathaniel et al.
Ahmad Almadhor et al.
Accurate identification and classification of 3D mesh data in medical imaging are crucial for various clinical and research applications, including surgical planning, anatomical analysis, and disease diagnosis. In recent years, the applicat...
CLNAD-Net: A Multi-Task Learning Framework for Cervical Lymph Node Computer-Aided Diagnosis Network [0.03%]
用于辅助诊断淋巴结的多任务学习网络框架CLNAD-Net
Weihua He,Fet Ouyang,Guangming Yang et al.
Weihua He et al.
The accurate diagnosis of cervical lymph node metastasis (CLNM) is critical for selecting appropriate treatment plans for patients with papillary thyroid cancer (PTC). Currently, diagnostic processes primarily rely on the expertise of ultra...
Large Language Models for Classifying Usual Interstitial Pneumonia from Radiology Reports: Native Reasoning Versus Structured Prompting [0.03%]
基于放射学报告的大语言模型间质性肺炎分类：原生推理与结构化提示
Ran Zhang,Thomas M Grist,Mark Schiebler et al.
Ran Zhang et al.
Extracting disease labels from radiology reports is essential for developing deep learning-based diagnostic models and enabling large-scale retrospective clinical research. Classification of usual interstitial pneumonia (UIP) patterns from ...
AI as Core Infrastructure in Radiology: Moving Beyond Pilots to Operational Excellence [0.03%]
人工智能在放射学中的核心基础设施作用：从试点项目迈向卓越运营
James Thannickal
James Thannickal
Artificial intelligence (AI) adoption in radiology has accelerated, but operational maturity has not kept pace. Many organisations still deploy AI as isolated point solutions, leading to fragmented workflows, duplicated integration work, in...