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...
Super-Resolution of Through-Plane Undersampled MRIs in Alzheimer's Disease Diagnosis [0.03%]
超分辨率在阿尔茨海默病诊断中通过平面 undersampled MRI的应用
Rosanna Turrisi,Simone Cammarasana,Martina Paccini et al.
Rosanna Turrisi et al.
Alzheimer's disease is a complex neurodegenerative disorder and the leading cause of dementia worldwide. Learning-based techniques applied to magnetic resonance imaging (MRI) have recently shown strong potential for automated diagnosis. Acc...
Patient-Level Cross-validated nnU-Net for Multiclass Segmentation of Lung Parenchyma and Solid Adenocarcinoma on Thoracic CT [0.03%]
基于胸部CT肺实质和实性腺癌多类分割的患者级交叉验证nnUNet方法
Achraf El Haouat,Hamza Sekkat,Othmane Amarhyouz et al.
Achraf El Haouat et al.
Automated segmentation of lung parenchyma and solid lung adenocarcinoma on thoracic computed tomography (CT) is needed for reproducible quantitative imaging, radiomics extraction, and treatment planning-related research. However, tumor segm...
Early Follicular Lymphoma Grading via PET-CT Fusion and Bayesian Deep Learning [0.03%]
基于PET-CT融合和贝叶斯深度学习的早期滤泡型淋巴瘤分级方法
Chunjun Qian,Lulu He,Qiuhui Jiang et al.
Chunjun Qian et al.
Accurate grading of follicular lymphoma (FL) is crucial for personalized treatment, but biopsy-based histopathology is invasive and limited by observer variability. To address these limits, we present an artificial intelligence framework fo...
Comparative Evaluation of Deep Generative Models for Predicting 12-Month Neovascular AMD Progression Using OCT and Fundus Photography [0.03%]
基于OCT和眼底照相的深度生成模型预测新生血管性年龄相关性黄斑变性一年内进展的比较研究
Fatma Sumer,Murat Toren,Berkutay Asan et al.
Fatma Sumer et al.
The purpose of this study is to systematically compare six deep generative models for predicting long-term anatomic progression of neovascular age-related macular degeneration (nAMD) from pretreatment retinal imaging. We retrospectively ana...
Multi-Frequency Feature Guided Progressive Divide-and-Conquer Network for Accelerated MRI Reconstruction [0.03%]
基于多频特征引导的快速分割与合并网络的加速MRI重建方法
Hanshuo Zhu,Xiaozhen Ren,Xiaqiong Fan et al.
Hanshuo Zhu et al.
Magnetic resonance imaging (MRI) is regarded as the clinical diagnostic gold standard. However, its lengthy scan times introduce motion artifacts, which can severely compromise diagnostic accuracy. K-space undersampling is a fundamental str...
AI-Assisted Papillary Thyroid Carcinoma Localization on Cervical Non-contrast CT: A Multicenter Validation and Two-Reader Pilot Study of a Standalone Executable nnU-Net Software [0.03%]
基于颈椎非对比度CT的乳头状甲状腺癌定位的AI辅助：独立可执行nnU-Net软件的多中心验证及两位读者的试点研究
Hao Wang,Xuan Wang,Zhi-Lin Chen et al.
Hao Wang et al.
Accurate preoperative localization and 3D anatomical assessment of papillary thyroid carcinoma (PTC) are critical for surgical decision-making. Cervical non-contrast CT (NCCT) avoids iodinated contrast-related risks but has limited PTC lesi...