نتایج جستجو برای: radiomics

تعداد نتایج: 1808  

2017
Fu-Sheng Ouyang Bao-Liang Guo Bin Zhang Yu-Hao Dong Lu Zhang Xiao-Kai Mo Wen-Hui Huang Shui-Xing Zhang Qiu-Gen Hu

There is no consensus on specific prognostic biomarkers potentially improving survival of nasopharyngeal carcinoma (NPC), especially in advanced-stage disease. The prognostic value of MRI-based radiomics signature is unclear. A total of 970 quantitative features were extracted from the tumor of 100 untreated NPC patients (stage III-IVb) (discovery set: n = 70, validation set: n = 30). We then a...

2017
Chen Shen Zhenyu Liu Min Guan Jiangdian Song Yucheng Lian Shuo Wang Zhenchao Tang Di Dong Lingfei Kong Meiyun Wang Dapeng Shi Jie Tian

OBJECTIVE To compare 2D and 3D radiomics features prognostic performance differences in CT images of non-small cell lung cancer (NSCLC). METHOD We enrolled 588 NSCLC patients from three independent cohorts. Two sets of 463 patients from two different institutes were used as the training cohort. The remaining cohort with 125 patients was set as the validation cohort. A total of 1014 radiomics ...

2016
Kaikai Wei Huifang Su Guofeng Zhou Rong Zhang Peiqiang Cai Yi Fan Chuanmiao Xie Baowei Fei Zhenfeng Zhang

A solitary pulmonary nodule is defined as radiographic lesion with diameters no more than 3 cm and completely surrounded by normal lung tissue. It is commonly encountered in clinical practice and its diagnosis is a big challenge. Medical imaging, as a non-invasive approach, plays a crucial role in the diagnosis of solitary pulmonary nodules since the potential morbidity of surgery and the limit...

Journal: :Journal of medical imaging 2017
Mohammad Javad Shafiee Audrey G. Chung Farzad Khalvati Masoom A. Haider Alexander Wong

While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concep...

2017
Kaixian Yu Youyi Zhang Yang Yu Chao Huang Rongjie Liu Tengfei Li Liuqing Yang Jeffrey S. Morris Veerabhadran Baladandayuthapani Hongtu Zhu

Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oroph...

2016
Panpan Hu Jiazhou Wang Haoyu Zhong Zhen Zhou Lijun Shen Weigang Hu Zhen Zhang

PURPOSE To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. RESULTS Volume normalized features are much more reproducible than unnormalized features. The average value of all slices is the most reproducible feature type in rectal cancer. Different filters have little effect ...

2017
Faiq A. Shaikh Omer Awan

Radiomics can be defined as the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with various modalities [1]. Radiomics methods can be applied across various cancers to identify tumor phenotype characteristics in the images that correlate with their likelihood of survival, as well as their association with the u...

2016
Rakesh Shiradkar Tarun K Podder Ahmad Algohary Satish Viswanath Rodney J Ellis Anant Madabhushi

BACKGROUND Radiomics or computer - extracted texture features have been shown to achieve superior performance than multiparametric MRI (mpMRI) signal intensities alone in targeting prostate cancer (PCa) lesions. Radiomics along with deformable co-registration tools can be used to develop a framework to generate targeted focal radiotherapy treatment plans. METHODS The Rad-TRaP framework compri...

2017
Yucheng Zhang Anastasia Oikonomou Alexander Wong Masoom A. Haider Farzad Khalvati

Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative features from radiological images. Radiomic features have been shown to provide prognostic value in predicting clinical outcomes in several studies. However, several challenges including feature redundancy, unbalanced data, and small sample sizes have led to relatively low predictive accuracy. In this study, we...

Journal: :Magnetic resonance imaging 2012
Virendra Kumar Yuhua Gu Satrajit Basu Anders Berglund Steven A Eschrich Matthew B Schabath Kenneth Forster Hugo J W L Aerts Andre Dekker David Fenstermacher Dmitry B Goldgof Lawrence O Hall Philippe Lambin Yoganand Balagurunathan Robert A Gatenby Robert J Gillies

"Radiomics" refers to the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with computed tomography, positron emission tomography or magnetic resonance imaging. Importantly, these data are designed to be extracted from standard-of-care images, leading to a very large potential subject pool. Radiomics data are in...

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