Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks [0.03%]
基于深度卷积神经网络的多中心多参数MR前列腺癌检测研究
Yohan Sumathipala,Nathan Lay,Baris Turkbey et al.
Yohan Sumathipala et al.
Multiparametric magnetic resonance imaging (mpMRI) of the prostate aids in early diagnosis of prostate cancer, but is difficult to interpret and subject to interreader variability. Our objective is to generate probability maps, overlaid on ...
Application of unsupervised learning to hyperspectral imaging of cardiac ablation lesions [0.03%]
无监督学习在心脏消融病变高光谱成像中的应用研究
Shuyue Guan,Huda Asfour,Narine Sarvazyan et al.
Shuyue Guan et al.
Atrial fibrillation is the most common cardiac arrhythmia. It is being effectively treated using the radiofrequency ablation (RFA) procedure, which destroys culprit tissue and creates scars that prevent the spread of abnormal electrical act...
Quantification of multiple mixed contrast and tissue compositions using photon-counting spectral computed tomography [0.03%]
基于光子计数的谱CT同时测量多种混比对比剂及组织的方法
Tyler E Curtis,Ryan K Roeder
Tyler E Curtis
Quantitative material decomposition of multiple mixed, or spatially coincident, contrast agent (gadolinium and iodine) and tissue (calcium and water) compositions is demonstrated using photon-counting spectral computed tomography (CT). Mate...
Tamara Miner Haygood,Samantha Smith,Jia Sun
Tamara Miner Haygood
The objective of our study was to determine how authors of published observer-performance experiments dealt with memory bias in study design. We searched American Journal of Roentgenology online and Radiology using "observer study" and "obs...
Eric Heim,Tobias Roß,Alexander Seitel et al.
Eric Heim et al.
Accurate segmentations in medical images are the foundations for various clinical applications. Advances in machine learning-based techniques show great potential for automatic image segmentation, but these techniques usually require a huge...
Small animal, positron emission tomography-magnetic resonance imaging system based on a clinical magnetic resonance imaging scanner: evaluation of basic imaging performance [0.03%]
基于临床磁共振成像仪的小动物正电子发射断层显微磁共振成像系统的基本图像性能评价
Raymond R Raylman,Patrick Ledden,Alexander V Stolin et al.
Raymond R Raylman et al.
Development of advanced preclinical imaging techniques has had an important impact on the field of biomedical research, with positron emission tomography (PET) imaging the most mature of these efforts. Developers of preclinical PET scanners...
Validation of automatic cochlear implant electrode localization techniques using [Formula: see text] [0.03%]
验证自动耳蜗植入电极定位技术的有效性使用[公式：见文本]
Yiyuan Zhao,Robert F Labadie,Benoit M Dawant et al.
Yiyuan Zhao et al.
Cochlear implants (CIs) are standard treatment for patients who experience sensorineural hearing loss. Although these devices have been remarkably successful at restoring hearing, it is rare that they permit to achieve natural fidelity and ...
Breast lesion classification based on dynamic contrast-enhanced magnetic resonance images sequences with long short-term memory networks [0.03%]
基于长短期记忆网络的乳腺动态增强磁共振图像序列表征及病变分类研究
Natalia Antropova,Benjamin Huynh,Hui Li et al.
Natalia Antropova et al.
We present a breast lesion classification methodology, based on four-dimensional (4-D) dynamic contrast-enhanced magnetic resonance images (DCE-MRI), using recurrent neural networks in combination with a pretrained convolutional neural netw...
Deep learning-based mesoscopic fluorescence molecular tomography: an in silico study [0.03%]
基于深度学习的介观荧光分子层析成像：仿真研究
Feixiao Long
Feixiao Long
Fluorescence molecular tomography (FMT), as well as mesoscopic FMT (MFMT) is widely employed to investigate molecular level processes ex vivo or in vivo. However, acquiring depth-localized and less blurry reconstruction still remains challe...
Classification of suspicious lesions on prostate multiparametric MRI using machine learning [0.03%]
基于机器学习的前列腺多参数MRI病变分类方法研究
Deukwoo Kwon,Isildinha M Reis,Adrian L Breto et al.
Deukwoo Kwon et al.
We present a radiomics-based approach developed for the SPIE-AAPM-NCI PROSTATEx challenge. The task was to classify clinically significant prostate cancer in multiparametric (mp) MRI. Data consisted of a "training dataset" (330 suspected le...