Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study [0.03%]
基于胸部X光片的深度学习模型筛查患者误识别错误：一项针对七名读者的研究
Kiduk Kim,Kyungjin Cho,Yujeong Eo et al.
Kiduk Kim et al.
We aimed to evaluate the ability of deep learning (DL) models to identify patients from a paired chest radiograph (CXR) and compare their performance with that of human experts. In this retrospective study, patient identification DL models ...
A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention [0.03%]
一种基于双分支结构和多尺度残差注意力的低剂量CT去噪网络
Ju Zhang,Lieli Ye,Weiwei Gong et al.
Ju Zhang et al.
Deep learning-based denoising of low-dose medical CT images has received great attention both from academic researchers and physicians in recent years, and has shown important application value in clinical practice. In this work, a novel tw...
Sex-Specific Imaging Biomarkers for Parkinson's Disease Diagnosis: A Machine Learning Analysis [0.03%]
基于机器学习的帕金森病诊断的性别特异性影像生物标志物研究
Yifeng Yang,Liangyun Hu,Yang Chen et al.
Yifeng Yang et al.
This study aimed to identify sex-specific imaging biomarkers for Parkinson's disease (PD) based on multiple MRI morphological features by using machine learning methods. Participants were categorized into female and male subgroups, and vari...
PelviNet: A Collaborative Multi-agent Convolutional Network for Enhanced Pelvic Image Registration [0.03%]
PelviNet：一种协作多智能体卷积网络用于增强盆腔图像配准
Rguibi Zakaria,Hajami Abdelmajid,Zitouni Dya et al.
Rguibi Zakaria et al.
PelviNet introduces a groundbreaking multi-agent convolutional network architecture tailored for enhancing pelvic image registration. This innovative framework leverages shared convolutional layers, enabling synchronized learning among agen...
Feasibility of Three-Dimension Chemical Exchange Saturation Transfer MRI for Predicting Tumor and Node Staging in Rectal Adenocarcinoma: An Exploration of Optimal ROI Measurement [0.03%]
三维化学交换饱和转移磁共振成像预测直肠腺癌肿瘤及淋巴结分期：最佳感兴趣区测量的探索性研究
Xiao Wang,Wenguang Liu,Ismail Bilal Masokano et al.
Xiao Wang et al.
To investigate the feasibility of predicting rectal adenocarcinoma (RA) tumor (T) and node (N) staging from an optimal ROI measurement using amide proton transfer weighted-signal intensity (APTw-SI) and magnetization transfer (MT) derived f...
Detection of Diabetic Retinopathy Using Discrete Wavelet-Based Center-Symmetric Local Binary Pattern and Statistical Features [0.03%]
基于离散小波的中心对称局部二值模式及统计特征的糖尿病视网膜病变检测方法研究
Imtiyaz Ahmad,Vibhav Prakash Singh,Manoj Madhava Gore
Imtiyaz Ahmad
Computer-aided diagnosis (CAD) system assists ophthalmologists in early diabetic retinopathy (DR) detection by automating the analysis of retinal images, enabling timely intervention and treatment. This paper introduces a novel CAD system b...
Correction: Certified Imaging Informatics Professionals (CIIP) Demonstrate Value to the Healthcare Industry and Focus on Quality Through the ABII 10-Year Requirements Practice Option [0.03%]
关于认证医学影像信息技术专家（CIIP）通过ABII十年要求实践选项展示对医疗保健行业的价值并致力于质量提升的更正公告
Ameena Elahi,Nikki Fennell,Liana Watson
Ameena Elahi
Published Erratum
Journal of imaging informatics in medicine. 2024 Sep 4. DOI:10.1007/s10278-024-01246-z 2024
Improving the Annotation Process in Computational Pathology: A Pilot Study with Manual and Semi-automated Approaches on Consumer and Medical Grade Devices [0.03%]
计算病理学中改进注释过程的试点研究：在消费级和医学级设备上采用手动和半自动方法的研究
Giorgio Cazzaniga,Fabio Del Carro,Albino Eccher et al.
Giorgio Cazzaniga et al.
The development of reliable artificial intelligence (AI) algorithms in pathology often depends on ground truth provided by annotation of whole slide images (WSI), a time-consuming and operator-dependent process. A comparative analysis of di...
Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies [0.03%]
低剂量CT去噪的无监督和自监督学习：训练策略的见解
Feixiang Zhao,Mingzhe Liu,Mingrong Xiang et al.
Feixiang Zhao et al.
In recent years, X-ray low-dose computed tomography (LDCT) has garnered widespread attention due to its significant reduction in the risk of patient radiation exposure. However, LDCT images often contain a substantial amount of noises, adve...
Application of Wiener Filter Based on Improved BB Gradient Descent in Iris Image Restoration [0.03%]
基于改进BB梯度下降的wiener滤波在 iris 图像复原中的应用研究
Chuandong Qin,Yiqing Zhang
Chuandong Qin
Iris recognition, renowned for its exceptional precision, has been extensively utilized across diverse industries. However, the presence of noise and blur frequently compromises the quality of iris images, thereby adversely affecting recogn...