Interpretable Whole-Breast Radiomic Biomarkers for Exploratory Assessment of HER2 + Breast Cancer in Digital Mammography [0.03%]
数字乳腺摄影中HER2阳性乳腺癌探索性评估的可解释全乳房放射组学生物标志物
Lucas de Brito Silva,Pedro Cunha Carneiro,Miguel Angel Guevara López et al.
Lucas de Brito Silva et al.
Breast cancer is a heterogeneous disease whose molecular subtypes differ in biological behavior, prognosis, and therapeutic response. This study investigated whether whole-breast radiomic features extracted from digital mammograms and showi...
Automated Detection of Taurodontism in Panoramic Radiographs Using a YOLOv8-Based Deep Learning Model [0.03%]
基于YOLOv8深度学习模型的全景片露齿症自动化检测方法研究
Merve Hacer Talu,Sümeyye Coşgun-Baybars,Rawan Aboalqaraya et al.
Merve Hacer Talu et al.
This study aimed to develop and evaluate a deep learning-based object detection system for the automated detection of taurodontism on panoramic radiographs using the You Only Look Once version 8 (YOLOv8) architecture and to compare the diag...
Deep Learning-Based Detection of Overhanging Restorations and Calculation of Radiographic Alveolar Bone Loss Percentage with YOLOv11 and YOLOv12 [0.03%]
基于深度学习的悬突检测及牙片骨丧失百分比计算（利用YOLOv11和YOLOv12）
Sukran Acipinar,Merve Aydogdu,Arzu Kockanat
Sukran Acipinar
The objective of this study is to evaluate the YOLOv11 and YOLOv12 deep learning models for the detection of overhanging restorations in panoramic radiographs and the calculation of the associated percentage of alveolar bone loss. Overhangi...
Advancing Data Privacy Under GDPR: A Bayesian Approach to Structured Risk Quantification in Medical DICOM Data [0.03%]
通用数据保护条例下的医疗DICOM数据的结构化风险量化及贝叶斯隐私防护方法研究
Santhosh Sankar
Santhosh Sankar
Under GDPR, protecting patient privacy is paramount. Yet, radiology departments routinely collect vast amounts of patient data to advance patient care and support medical research. The majority of this collected data are stored in DICOM for...
Foundation Models and AI Agents in Digital Pathology Imaging: A Systematic Review of Integration into the Clinical Workflow and Implementation Challenges [0.03%]
基础模型和人工智能代理在数字病理学影像中的整合与实施挑战：系统综述
Ye Chen,Xiaoqun Qin,Shouping Chen
Ye Chen
The objective of this study is to systematically assess foundation model‑driven AI agents in digital pathology imaging, focusing on technical progress, clinical validation, and workflow integration barriers from an implementation science p...
Effectiveness of Artificial Intelligence in the Automatic Diagnosis of Lesions Detected in Panoramic Radiographs [0.03%]
人工智能在曲面体层像中病灶自动诊断中的有效性研究
Zarif Ece Hammudioğlu,Ceren Aktuna Belgin,Kaan Orhan et al.
Zarif Ece Hammudioğlu et al.
This study was aimed at evaluating the effectiveness of artificial intelligence (AI) in detecting jaw cysts and tumors, analyzing lesion content, and establishing diagnoses on panoramic radiographs. To construct the dataset, panoramic radio...
Agreement Between Semi-Automated CT-Based Body Composition Software and Qualitative Muscle Assessment in Sarcopenia: A Comparative Study in Abdominal Malignancies [0.03%]
基于CT的半自动身体成分分析软件与肌少症定性肌肉评估之间的相关性：腹部恶性肿瘤患者的比较研究
Ahmet Gazi Acar,Hatice Tuba Sanal
Ahmet Gazi Acar
To compare quantitative muscle and adipose tissue parameters obtained using two semi-automated CT-based body composition analysis software tools and to evaluate their association with qualitative muscle assessment using the Goutallier class...
TriNet-MoE: One New Neural Network Framework Based on Mixture of Experts for CXR-Based COVID-19 Detection [0.03%]
基于专家混合框架的CXR图像新冠病灶神经网络检测方法研究
Chunhua Zhu,Shuzhi Yang,Xue Li
Chunhua Zhu
As a low-dose portable imaging technology, chest X-ray (CXR) is widely used for the screening of lung diseases, including COVID-19. However, existing deep learning methods for CXR-based COVID-19 detection and common pneumonia recognition st...
Multi-scale Radiomic Fingerprint: Quantifying Spatial Changes in Biology [0.03%]
多尺度影像组学指纹：量化生物学的时空变化特征
Samuel Lefcourt,Alan Kim,Peng Huang et al.
Samuel Lefcourt et al.
Traditional radiomic studies build texture matrices using single-voxel increments. However, useful information may emerge when radiomic features are instead evaluated across multiple spatial scales. Moreover, basing these scales on physical...
A Spatiotemporal Transformer Framework on 4D-CT for Early Prediction of Progressive Pulmonary Fibrosis [0.03%]
基于4D-CT的时空变换框架在进行期肺纤维化的早期预测中的应用
Zahra Raeisi,Ali Gholami,Saber Mardkardideh et al.
Zahra Raeisi et al.
Progressive pulmonary fibrosis (PPF) remains difficult to predict because static imaging may not fully capture regional respiratory motion, ventilation heterogeneity, and mechanical deformation. We propose a spatiotemporal transformer (ST-F...