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...
Biomarker-Conditioned Vision Transformers with Deformable Biomarker Attention for Alzheimer's Disease Classification [0.03%]
基于可变形生物标志物注意力的生物标志物条件视觉变换器阿尔茨海默病分类方法
Mohammed G Alsubaie,Suhuai Luo,Kamran Shaukat et al.
Mohammed G Alsubaie et al.
Alzheimer's disease (AD) classification from structural magnetic resonance imaging (MRI) remains challenging, particularly when distinguishing mild cognitive impairment (MCI) from both cognitively normal (CN) ageing and established AD. Mult...
Multimodal Large Language Models for Breast Ultrasound Report Auditing: Workflow-Error Detection, False-Positive Burden, and Limits of Key-Image Interpretation [0.03%]
多模态大型语言模型在乳腺超声报告审核中的应用：工作流错误检测、假阳性负担及关键图像解读的局限性
Mi Zou,Mengsu Xiao,Qingli Zhu et al.
Mi Zou et al.
Large language models (LLMs) are increasingly being evaluated for radiology reporting. However, the incremental value of adding report-embedded key images to report text for breast ultrasound report auditing remains unclear. This retrospect...
User Interface Design for AI-Based Medical Imaging: A Scoping Review [0.03%]
基于人工智能的医学影像的用户界面设计：范围性综述
Isabela Cristina Amaro Souza,Lilian Berton
Isabela Cristina Amaro Souza
While the graphical user interface (GUI) is fundamental to computer-aided diagnosis (CAD) systems, a significant void exists in the technical literature regarding its design and integration into clinical workflows. Bridging this gap is esse...
Retrieval-Augmented Generation in Radiology: A Scoping Review of Architectures, Imaging Applications, and Directions for Equitable Deployment [0.03%]
放射学中的检索增强生成：架构、影像应用及公平部署方向的综述性回顾
Matthew Yu Heng Wong,Huitao Li,Curtis Langlotz et al.
Matthew Yu Heng Wong et al.
Large language models (LLMs) are increasingly explored in radiology, yet concerns persist regarding hallucination and lack of factual grounding. Retrieval-augmented generation (RAG) seeks to address these limitations by coupling generative ...