A Large Language Model to Detect Negated Expressions in Radiology Reports [0.03%]
用于检测放射学报告中否定表达的大规模语言模型
Yvonne Su,Yonatan B Babore,Charles E Kahn Jr
Yvonne Su
Natural language processing (NLP) is crucial to extract information accurately from unstructured text to provide insights for clinical decision-making, quality improvement, and medical research. This study compared the performance of a rule...
Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence [0.03%]
基于人工智能的超声引导腰方阻滞自动划分技术
Qiang Wang,Bingxi He,Jie Yu et al.
Qiang Wang et al.
Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surgeries. Due to the anatomical complexity and individual variability of the quadratus lumborum...
Cross-site Validation of AI Segmentation and Harmonization in Breast MRI [0.03%]
跨站点验证乳腺MRI中的人工智能分割和标准化技术
Yu Huang,Nicholas J Leotta,Lukas Hirsch et al.
Yu Huang et al.
This work aims to perform a cross-site validation of automated segmentation for breast cancers in MRI and to compare the performance to radiologists. A three-dimensional (3D) U-Net was trained to segment cancers in dynamic contrast-enhanced...
A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma Based on CT Images [0.03%]
基于CT图像的肾细胞癌病理分类的不确定性估计的鲁棒深度学习方法
Ni Yao,Hang Hu,Kaicong Chen et al.
Ni Yao et al.
This study developed and validated a deep learning-based diagnostic model with uncertainty estimation to aid radiologists in the preoperative differentiation of pathological subtypes of renal cell carcinoma (RCC) based on computed tomograph...
Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles [0.03%]
基于深度集成的双视图乳腺X射线图像配准不确定度估计
William C Walton,Seung-Jun Kim
William C Walton
Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)-based methods for registering the locations of lesions between the craniocaudal (CC) and mediolateral oblique (MLO) mammographic X-ray imag...
A Self-Supervised Equivariant Refinement Classification Network for Diabetic Retinopathy Classification [0.03%]
自监督等变精炼分类网络的糖尿病视网膜病变分类方法
Jiacheng Fan,Tiejun Yang,Heng Wang et al.
Jiacheng Fan et al.
Diabetic retinopathy (DR) is a retinal disease caused by diabetes. If there is no intervention, it may even lead to blindness. Therefore, the detection of diabetic retinopathy is of great significance for preventing blindness in patients. M...
Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population [0.03%]
儿童不是成人的缩小版：解决成人深度学习CT器官分割模型在儿科人群中的有限适用性问题
Devina Chatterjee,Adway Kanhere,Florence X Doo et al.
Devina Chatterjee et al.
Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the performance of TotalSegmentator, a state-of-the-art adult-trained CT organ segmentation mod...
Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index [0.03%]
基于深度学习的图像重建技术对冠脉CTA图像质量及冠状动脉周围脂肪CT值的影响研究
Junqing Mei,Chang Chen,Ruoting Liu et al.
Junqing Mei et al.
To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-...
Intra-Individual Reproducibility of Automated Abdominal Organ Segmentation-Performance of TotalSegmentator Compared to Human Readers and an Independent nnU-Net Model [0.03%]
自动腹部器官分割的组内可重复性：TotalSegmentator与人工阅片及独立nnU-Net模型的表现比较
Lorraine Abel,Jakob Wasserthal,Manfred T Meyer et al.
Lorraine Abel et al.
The purpose of this study is to assess segmentation reproducibility of artificial intelligence-based algorithm, TotalSegmentator, across 34 anatomical structures using multiphasic abdominal CT scans comparing unenhanced, arterial, and porta...
Teleradiology-Based Referrals for Patients with Gastroenterological Diseases Between Tertiary and Regional Hospitals: A Hospital-to-Hospital Approach [0.03%]
基于远程放射学的三级医院与区域医院之间的胃肠病患者会诊：医院对医院的方法
Kosuke Suzuki,Hiroaki Saito,Yoshika Saito et al.
Kosuke Suzuki et al.
Teleradiology is recognized for fostering collaboration between regional and tertiary hospitals. However, its application in gastroenterological diseases remains underexplored. This study aimed to assess the effectiveness of teleradiology i...