Deep Learning on Tumor Habitat Sub-regions vs. Whole-Tumor ROI: A Comparative Study of Fusion Strategies for Breast Cancer Molecular Subtype Prediction [0.03%]
基于肿瘤生长环境的亚区域和整个肿瘤感兴趣区的深度学习方法比较研究：乳腺癌分子亚型预测融合策略的对比研究
Yujiao Yang,Xiaotao Qin,Xia Zou et al.
Yujiao Yang et al.
This study aimed to compare deep learning models based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) whole-tumor and habitat regions of interest (ROIs) for non-invasive preoperative luminal subtype prediction in invasive...
Deep Learning vs. Traditional Machine Learning in the Diagnosis of Cutaneous Drug Eruptions: A Comparative Study with Explainable AI on Whole-Slide Images [0.03%]
深度学习与传统机器学习在药物性皮炎诊断中的比较研究：具有可解释性的AI在全滑动图像上的应用研究
Ayşe Türkmen Dedeoğlu,Hüseyin Yanık,Erdem Uysal et al.
Ayşe Türkmen Dedeoğlu et al.
Histopathological diagnosis of cutaneous drug eruptions (CDEs) presents a challenge in dermatopathology due to morphological overlap and high inter-observer variability. This retrospective study systematically compares the diagnostic perfor...
Considerations for Pre-deployment Planning in Point-of-Care Ultrasound Program Implementation: A HIMSS-SIIM Enterprise Imaging Community Whitepaper in Collaboration with AIUM [0.03%]
基于护理点超声波计划实施的预部署规划考虑：HIMSS-SIIM企业成像社区白皮书与AIUM合作編制
Allan Bottemiller,Robinson M Ferre,Les R Folio et al.
Allan Bottemiller et al.
Point-of-care ultrasound (POCUS) provides real-time diagnostic capabilities at the bedside. Implementing a POCUS program in an institution is a highly complex process. Coordinating the imaging workflow of numerous clinical specialties requi...
Self-supervised Depth Estimation for Monocular Endoscopy Using Confidence-Rectified Distillation and Semantic Distribution Alignment [0.03%]
基于自信蒸馏和语义分布对齐的单目内窥镜自监督深度估计方法
Zhongping Li,Kejin Zhu,Guozhe Jin
Zhongping Li
Monocular depth estimation (MDE) is a core capability for 3D reconstruction and intraoperative augmented reality in endoscopy. Recent self-supervised methods improve performance by leveraging reprojection consistency, temporal constraints, ...
Rules-Augmented GLM-5.1 Prompting for Four-Class Chest CT Protocol Selection [0.03%]
基于规则的GLM-5.1提示用于四类胸部CT协议选择
Kartik Gupta,Jaron Chong
Kartik Gupta
Rule-augmented large language models (LLMs) may support radiology protocol selection, but their value in small, imbalanced local tasks remains uncertain. We evaluated whether GLM-5.1 prompting remained competitive with classical text classi...
A Framework with Transformer-Based Model for Cerebrovascular Stenosis Detection in Magnetic Resonance Angiography [0.03%]
基于Transformer模型的磁共振血管造影颈动脉狭窄检测框架
Duc-Khanh Nguyen,Chien-Lung Chan,Chien-Wei Huang et al.
Duc-Khanh Nguyen et al.
Accurate identification of cerebrovascular stenosis is essential for early stroke prevention and effective clinical management. Magnetic resonance angiography provides non-invasive 3D visualization of cerebral vessels, but reliable automate...
AI-Assisted Classification of Mandibular First Molars According to the Presence of an Additional Distal Canal on CBCT Images: Automated CBCT Mandibular Canal Detection [0.03%]
基于CBCT图像辅助下颌第一磨牙额外远中根管的分类：自动化CBCT下颌第二磨牙远中根管检测
Eda Gursu Sahin,Zuhal Ovuz,Zafer Civelek et al.
Eda Gursu Sahin et al.
A hybrid fusion architecture based on deep convolutional neural networks (CNNs) was implemented for AI-assisted classification of mandibular first molars (MFMs) according to the presence or absence of an additional distal canal on cone-beam...
Abdominal Dual-Energy CT with Deep Learning Reconstruction: Preserving Image Quality and Hepatic Lesion Conspicuity with Reduced Radiation and Contrast [0.03%]
基于深度学习的腹腔双能量CT重建技术降低辐射及对比剂剂量而不影响图像质量和肝部病灶显示力
Borong Tang,Wanyi Zheng,Xiaojuan Lin et al.
Borong Tang et al.
The objective was to evaluate the image quality and hepatic lesion conspicuity in a dual-low-dose (radiation and contrast volume) upper abdominal dual-energy CT (DECT) protocol utilizing deep learning image reconstruction (DLIR). After prop...
AI-Driven Preoperative Chest Radiograph Analysis for Prognostic Stratification in Surgically Resected Pathological Stage 1 Non-Small Cell Lung Cancer [0.03%]
基于人工智能的术前胸部X线片分析在I期非小细胞肺癌病理分期中的预后分层作用
Hyun Joo Shin,Eun Hye Lee,Se Hyun Kwak et al.
Hyun Joo Shin et al.
The purpose of the study is to investigate the potential of artificial intelligence (AI)-driven analysis of preoperative chest radiograph (CXR) for predicting postoperative outcome in patients with early-stage non-small cell lung cancer (NS...
Transformer and Attention Enhanced Deep Learning Approach for CBCT-Based Mental Foramen Classification and Segmentation [0.03%]
基于CBCT的下颌孔分类和分割的变压器和注意增强深度学习方法
Osman Güler,Mustafa Teke,Zafer Civelek
Osman Güler
Determining the location and morphological characteristics of the mental foramen is of critical clinical importance in dental surgical procedures. In this study, the mental foramen was classified and segmented using deep learning methods on...