Nanoscale x-ray holotomography of human brain tissue with phase retrieval based on multienergy recordings [0.03%]
基于多能量记录的相位恢复的人脑组织纳米x射线全息层析成像
Anna-Lena Robisch,Marina Eckermann,Mareike Töpperwien et al.
Anna-Lena Robisch et al.
X-ray cone-beam holotomography of unstained tissue from the human central nervous system reveals details down to subcellular length scales. This visualization of variations in the electron density of the sample is based on phase-contrast te...
Deep learning-based segmentation of malignant pleural mesothelioma tumor on computed tomography scans: application to scans demonstrating pleural effusion [0.03%]
基于深度学习的计算机断层扫描上恶性间皮瘤肿瘤分割：在显示胸腔积液的扫描上的应用
Eyjolfur Gudmundsson,Christopher M Straus,Feng Li et al.
Eyjolfur Gudmundsson et al.
Tumor volume is a topic of interest for the prognostic assessment, treatment response evaluation, and staging of malignant pleural mesothelioma. Many mesothelioma patients present with, or develop, pleural fluid, which may complicate the se...
Toward point-of-care ultrasound estimation of fetal gestational age from the trans-cerebellar diameter using CNN-based ultrasound image analysis [0.03%]
基于CNN的超声图像分析在胎儿小脑经线测量中的应用研究
Mohammad A Maraci,Mohammad Yaqub,Rachel Craik et al.
Mohammad A Maraci et al.
Obstetric ultrasound is a fundamental ingredient of modern prenatal care with many applications including accurate dating of a pregnancy, identifying pregnancy-related complications, and diagnosis of fetal abnormalities. However, despite it...
Parallel implementations to accelerate the autofocus process in microscopy applications [0.03%]
用于显微镜自动聚焦的并行实现方法研究
Juan C Valdiviezo-N,Francisco J Hernandez-Lopez,Carina Toxqui-Quitl
Juan C Valdiviezo-N
Several autofocus algorithms based on the analysis of image sharpness have been proposed for microscopy applications. Since autofocus functions (AFs) are computed from several images captured at different lens positions, these algorithms ar...
Melissa Treviño,Baris Turkbey,Bradford J Wood et al.
Melissa Treviño et al.
Radiologists can identify whether a radiograph is abnormal or normal at above chance levels in breast and lung images presented for half a second or less. This early perceptual processing has only been demonstrated in static two-dimensional...
Maryellen Giger
Maryellen Giger
An editorial by Editor-in-Chief Maryellen Giger explains the journal's transition to structured abstracts. © 2020 Society of Photo-Optical Instrumentati...
Soham Banerjee,Trafton Drew,Megan K Mills et al.
Soham Banerjee et al.
Prior research has demonstrated that perceptual training can improve the ability of healthcare trainees in identifying abnormalities on medical images, but it is unclear if the improved performance is due to learning or attentional shift-th...
Ethan Du-Crow,Susan M Astley,Johan Hulleman
Ethan Du-Crow
Computer-aided detection (CAD) systems are used to aid readers interpreting screening mammograms. An expert reader searches the image initially unaided and then once again with the aid of CAD, which prompts automatically detected suspicious...
Coronary calcification segmentation in intravascular OCT images using deep learning: application to calcification scoring [0.03%]
基于深度学习的冠状动脉钙化血管内OCT图像分割及其在评价钙化程度中的应用研究
Yazan Gharaibeh,David Prabhu,Chaitanya Kolluru et al.
Yazan Gharaibeh et al.
Major calcifications are of great concern when performing percutaneous coronary interventions because they inhibit proper stent deployment. We created a comprehensive software to segment calcifications in intravascular optical coherence tom...
Automatic segmentation of all lower limb muscles from high-resolution magnetic resonance imaging using a cascaded three-dimensional deep convolutional neural network [0.03%]
基于级联三维深度卷积神经网络的高分辨率磁共振图像下肢全部肌肉自动化分割方法
Renkun Ni,Craig H Meyer,Silvia S Blemker et al.
Renkun Ni et al.
High-resolution magnetic resonance imaging with fat suppression can obtain accurate anatomical information of all 35 lower limb muscles and individual segmentation can facilitate quantitative analysis. However, due to limited contrast and e...