Video compression to support the expansion of whole-slide imaging into cytology [0.03%]
用于支持全视屏成像向细胞学扩展的视频压缩技术
Mark D Zarella,Jennifer Jakubowski
Mark D Zarella
Digital screening and diagnosis from cytology slides can be aided by capturing multiple focal planes. However, using conventional methods, the large file sizes of high-resolution whole-slide images increase linearly with the number of focal...
Detecting mammographically occult cancer in women with dense breasts using deep convolutional neural network and Radon Cumulative Distribution Transform [0.03%]
使用深度卷积神经网络和Radon累积分布变换检测致密型乳腺中隐藏的癌症
Juhun Lee,Robert M Nishikawa
Juhun Lee
We have applied the Radon Cumulative Distribution Transform (RCDT) as an image transformation to highlight the subtle difference between left and right mammograms to detect mammographically occult (MO) cancer in women with dense breasts and...
Chia-Chien Wu,Nicholas M D&#x;Ardenne,Robert M Nishikawa et al.
Chia-Chien Wu et al.
Evans et al. (2016) showed that radiologists can classify the mammograms as normal or abnormal at above-chance levels after a 250-ms exposure. Our study documents a similar gist signal in digital breast tomosynthesis (DBT) images. DBT is a ...
Learning-based deformable image registration: effect of statistical mismatch between train and test images [0.03%]
基于学习的可变形图像配准：训练集和测试集统计特性差异的影响
Michael D Ketcha,Tharindu De Silva,Runze Han et al.
Michael D Ketcha et al.
Convolutional neural networks (CNNs) offer a promising means to achieve fast deformable image registration with accuracy comparable to conventional, physics-based methods. A persistent question with CNN methods, however, is whether they wil...
Translation of adapting quantitative CT data from research to local clinical practice: validation evaluation of fully automated procedures to provide lung volumes and percent emphysema [0.03%]
自研究转化至临床的定量CT数据适配的翻译：全自动提供肺容积和肺气肿百分比程序的验证评估
Krystle M Leung,Douglas Curran-Everett,Elizabeth A Regan et al.
Krystle M Leung et al.
Current clinical chest CT reporting includes limited qualitative assessment of emphysema with rare mention of lung volumes and limited reporting of emphysema, based upon retrospective review of CT reports. Quantitative CT analysis performed...
Impact of blue light filtering glasses on computer vision syndrome in radiology residents: a pilot study [0.03%]
抗蓝光眼镜对放射学住院医师计算机视觉综合征影响的试点研究
Alexander Dabrowiecki,Alexander Villalobos,Elizabeth A Krupinski
Alexander Dabrowiecki
Computer vision syndrome (CVS) is an umbrella term for a pattern of symptoms associated with prolonged digital screen exposure, such as eyestrain, headaches, blurred vision, and dry eyes. Commercially available blue light filtering lenses (...
Histopathologist-level quantification of Ki-67 immunoexpression in gastroenteropancreatic neuroendocrine tumors using semiautomated method [0.03%]
使用半自动方法对胃肠胰神经内分泌肿瘤中的Ki-67免疫表达进行类病理医师水平的量化评估
Heba Saadeh,Niveen Abdullah,Madiha Erashdi et al.
Heba Saadeh et al.
The role of Ki-67 index in determining the prognosis and management of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has become more important yet presents a challenging assessment dilemma. Although the precise method of Ki-67 ind...
Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning [0.03%]
基于MRI和深度学习的脑肿瘤异柠檬酸脱氢酶状态分类
Sahil Nalawade,Gowtham K Murugesan,Maryam Vejdani-Jahromi et al.
Sahil Nalawade et al.
Isocitrate dehydrogenase (IDH) mutation status is an important marker in glioma diagnosis and therapy. We propose an automated pipeline for noninvasively predicting IDH status using deep learning and T2-weighted (T2w) magnetic resonance (MR...
Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities [0.03%]
拟人化左心室网格体模：使用相干点漂移法研究SQUEEZ检测局部室壁运动异常准确性的框架
Ashish Manohar,Gabrielle M Colvert,Andrew Schluchter et al.
Ashish Manohar et al.
We present an anthropomorphically accurate left ventricular (LV) phantom derived from human computed tomography (CT) data to serve as the ground truth for the optimization and the spatial resolution quantification of a CT-derived regional s...
Using deep learning for a diffusion-based segmentation of the dentate nucleus and its benefits over atlas-based methods [0.03%]
基于深度学习的齿状核扩散分割及其相对于图谱法的优势
Camilo Bermudez Noguera,Shunxing Bao,Kalen J Petersen et al.
Camilo Bermudez Noguera et al.
The dentate nucleus (DN) is a gray matter structure deep in the cerebellum involved in motor coordination, sensory input integration, executive planning, language, and visuospatial function. The DN is an emerging biomarker of disease, infor...