Performance of angiographic parametric imaging in locating infarct core in large vessel occlusion acute ischemic stroke patients [0.03%]
大型动脉闭塞急性缺血性卒中患者血管造影参数成像定位梗死核心的效果
Ryan A Rava,Maxim Mokin,Kenneth V Snyder et al.
Ryan A Rava et al.
Purpose: Biomarkers related to hemodynamics can be quantified using angiographic parametric imaging (API), which is a quantitative imaging method that uses digital subtraction angiography (DSA). We aimed to assess the accuracy of API in loc...
Anatomically consistent CNN-based segmentation of organs-at-risk in cranial radiotherapy [0.03%]
基于CNN的颅脑放疗危及器官解剖一致性分割方法研究
Pawel Mlynarski,Hervé Delingette,Hamza Alghamdi et al.
Pawel Mlynarski et al.
Planning of radiotherapy involves accurate segmentation of a large number of organs at risk (OAR), i.e., organs for which irradiation doses should be minimized to avoid important side effects of the therapy. We propose a deep learning metho...
External validation of a mammographic texture marker for breast cancer risk in a case-control study [0.03%]
一项病例对照研究中乳腺癌风险乳图纹理标志的外部验证
Chao Wang,Adam R Brentnall,James Mainprize et al.
Chao Wang et al.
Purpose: The pattern of dense tissue on a mammogram appears to provide additional information than overall density for risk assessment, but there has been little consistency in measures of texture identified. The purpose of this study is th...
Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle study [0.03%]
深度学习可以被用来训练新手非专业人士去辨别乳房X线片中某些癌症的诊断型视觉特征：概念验证型研究
Jay Hegdé
Jay Hegdé
The scientific, clinical, and pedagogical significance of devising methodologies to train nonprofessional subjects to recognize diagnostic visual patterns in medical images has been broadly recognized. However, systematic approaches to doin...
Interpretation time for screening mammography as a function of the number of computer-aided detection marks [0.03%]
乳腺筛查中根据计算机辅助检测标志数量而变化的阅片时间
Tayler M Schwartz,Stephen L Hillis,Radhika Sridharan et al.
Tayler M Schwartz et al.
Purpose: Computer-aided detection (CAD) alerts radiologists to findings potentially associated with breast cancer but is notorious for creating false-positive marks. Although a previous paper found that radiologists took more time to interp...
Deep convolutional neural networks in the classification of dual-energy thoracic radiographic views for efficient workflow: analysis on over 6500 clinical radiographs [0.03%]
基于深度卷积神经网络的双能量胸部X射线影像分类方法：基于6500余张临床X射片的研究分析
Jennie Crosby,Thomas Rhines,Feng Li et al.
Jennie Crosby et al.
DICOM header information is frequently used to classify medical image types; however, if a header is missing fields or contains incorrect data, the utility is limited. To expedite image classification, we trained convolutional neural networ...
Automatic generation of three-dimensional dose reconstruction data for two-dimensional radiotherapy plans for historically treated patients [0.03%]
基于历史治疗患者的二维放疗计划的三维剂量重建数据的自动生成功能
Ziyuan Wang,Marco Virgolin,Peter A N Bosman et al.
Ziyuan Wang et al.
Performing large-scale three-dimensional radiation dose reconstruction for patients requires a large amount of manual work. We present an image processing-based pipeline to automatically reconstruct radiation dose. The pipeline was designed...
Efficient directionality-driven dictionary learning for compressive sensing magnetic resonance imaging reconstruction [0.03%]
一种高效的压缩感知磁共振成像重建的方向性字典学习方法
Anupama Arun,Thomas James Thomas,J Sheeba Rani et al.
Anupama Arun et al.
Compressed sensing is an acquisition strategy that possesses great potential to accelerate magnetic resonance imaging (MRI) within the ambit of existing hardware, by enforcing sparsity on MR image slices. Compared to traditional reconstruct...
Influence of background lung characteristics on nodule detection with computed tomography [0.03%]
背景肺特征对CT检出肺结节的影响研究
Boning Li,Taylor B Smith,Kingshuk R Choudhury et al.
Boning Li et al.
We sought to characterize local lung complexity in chest computed tomography (CT) and to characterize its impact on the detectability of pulmonary nodules. Forty volumetric chest CT scans were created by embedding between three and five sim...
Evaluation of image quality and task performance for a mobile C-arm with a complementary metal-oxide semiconductor detector [0.03%]
具有CMOS检测器的移动C形臂图像质量与任务表现评估研究
Godwin O Abiola,Niral M Sheth,Wojciech Zbijewski et al.
Godwin O Abiola et al.
We assessed interventional radiologists' task-based image quality preferences for two- and three-dimensional images obtained with a complementary metal-oxide semiconductor (CMOS) flat-panel detector versus a hydrogenated amorphous silicon (...