Impact of JPEG 2000 compression on deep convolutional neural networks for metastatic cancer detection in histopathological images [0.03%]
JPEG 2000压缩对组织病理图像中转移性癌症检测的深度卷积神经网络的影响
Farhad Ghazvinian Zanjani,Svitlana Zinger,Bastian Piepers et al.
Farhad Ghazvinian Zanjani et al.
The availability of massive amounts of data in histopathological whole-slide images (WSIs) has enabled the application of deep learning models and especially convolutional neural networks (CNNs), which have shown a high potential for improv...
Glioma grading using structural magnetic resonance imaging and molecular data [0.03%]
结合结构磁共振和分子数据的胶质瘤分级研究
Syed M S Reza,Manar D Samad,Zeina A Shboul et al.
Syed M S Reza et al.
A glioma grading method using conventional structural magnetic resonance image (MRI) and molecular data from patients is proposed. The noninvasive grading of glioma tumors is obtained using multiple radiomic texture features including dynam...
Boundary determination of foot ulcer images by applying the associative hierarchical random field framework [0.03%]
基于关联层次化随机域的糖尿病足溃疡边界定位方法
Lei Wang,Peder C Pedersen,Emmanuel Agu et al.
Lei Wang et al.
As traditional visual-examination-based methods provide neither reliable nor consistent wound assessment, several computer-based approaches for quantitative wound image analysis have been proposed in recent years. However, these methods req...
Distance canonical correlation analysis with application to an imaging-genetic study [0.03%]
具有应用遗传影像学研究的_DISTANCE_典范相关分析
Wenxing Hu,Aiying Zhang,Biao Cai et al.
Wenxing Hu et al.
Distance correlation is a measure that can detect both linear and nonlinear associations. However, applying distance correlation to imaging genetic studies often needs multiple testing correction due to the large number of multiple inferenc...
Automatic skin lesion segmentation by coupling deep fully convolutional networks and shallow network with textons [0.03%]
基于深度全卷积网络和使用超像素的浅层网络相结合的皮肤病变区域自动分割算法
Lei Zhang,Guang Yang,Xujiong Ye
Lei Zhang
Segmentation of skin lesions is an important step in computer-aided diagnosis of melanoma; it is also a very challenging task due to fuzzy lesion boundaries and heterogeneous lesion textures. We present a fully automatic method for skin les...
Intraoperative 360-deg three-dimensional transvaginal ultrasound during needle insertions for high-dose-rate transperineal interstitial gynecologic brachytherapy of vaginal tumors [0.03%]
高剂量率经会阴介入阴道肿瘤妇科腔内放疗过程中超声引导探头旋转360度的三维经阴道超声图像显示及穿刺定位评估
Jessica Robin Rodgers,Jeffrey Bax,Kathleen Surry et al.
Jessica Robin Rodgers et al.
Brachytherapy, a type of radiotherapy, may be used to place radioactive sources into or in close proximity to tumors, providing a method for conformally escalating dose in the tumor and the local area surrounding the malignancy. High-dose-r...
Erratum: Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network [0.03%]
致读者一封信：标准化摄取值偏差的时变性测量及其修正方法
Darrin Byrd,Rebecca Christopfel,Grae Arabasz et al.
Darrin Byrd et al.
[This corrects the article DOI: 10.1117/1.JMI.5.1.011016.].
Md Zahangir Alom,Chris Yakopcic,Mahmudul Hasan et al.
Md Zahangir Alom et al.
Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation,...
Systematic analysis of bias and variability of morphologic features for lung lesions in computed tomography [0.03%]
肺癌病变的系统性分析：CT影像学特征的偏倚和变异分析
Jocelyn Hoye,Justin Solomon,Thomas J Sauer et al.
Jocelyn Hoye et al.
We propose to characterize the bias and variability of quantitative morphology features of lung lesions across a range of computed tomography (CT) imaging conditions. A total of 15 lung lesions were simulated (five in each of three spiculat...
Breast cancer detection using synthetic mammograms from generative adversarial networks in convolutional neural networks [0.03%]
基于生成对抗网络和卷积神经网络的乳腺癌检测方法研究
Shuyue Guan,Murray Loew
Shuyue Guan
The convolutional neural network (CNN) is a promising technique to detect breast cancer based on mammograms. Training the CNN from scratch, however, requires a large amount of labeled data. Such a requirement usually is infeasible for some ...