Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
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How to use CT texture analysis for prognostication of non-small cell lung cancerCT texture analysis using the filtration-histogram method: what do the measurements mean?Quantifying tumour heterogeneity with CTDevelopment of a nomogram combining clinical staging with (18)F-FDG PET/CT image features in non-small-cell lung cancer stage I-IIIPET/CT in Oncology: Current Status and Perspectives.The use of molecular imaging combined with genomic techniques to understand the heterogeneity in cancer metastasis.High quality machine-robust image features: identification in nonsmall cell lung cancer computed tomography imagesCT-based radiomic signature predicts distant metastasis in lung adenocarcinomaRadiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer.Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer.Robust Radiomics feature quantification using semiautomatic volumetric segmentation.Predicting adenocarcinoma recurrence using computational texture models of nodule components in lung CT.Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy.Texture Analysis of Non-Contrast-Enhanced Computed Tomography for Assessing Angiogenesis and Survival of Soft Tissue Sarcoma.Machine Learning methods for Quantitative Radiomic Biomarkers.Early Change in Metabolic Tumor Heterogeneity during Chemoradiotherapy and Its Prognostic Value for Patients with Locally Advanced Non-Small Cell Lung Cancer.Texture analysis of (125)I-A5B7 anti-CEA antibody SPECT differentiates metastatic colorectal cancer model phenotypes and anti-vascular therapy response.Tumor Heterogeneity in Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Advanced Gastric Cancer Assessed by CT Texture Analysis: Association with Survival after Trastuzumab Treatment.Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer.Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?Stage III Non-Small Cell Lung Cancer: Prognostic Value of FDG PET Quantitative Imaging Features Combined with Clinical Prognostic FactorsUncertainty analysis of quantitative imaging features extracted from contrast-enhanced CT in lung tumors.Role of quantitative computed tomography texture analysis in the differentiation of primary lung cancer and granulomatous nodules.CT texture analysis in colorectal liver metastases: A better way than size and volume measurements to assess response to chemotherapy?MRI texture analysis parameters of contrast-enhanced T1-weighted images of Crohn's disease differ according to the presence or absence of histological markers of hypoxia and angiogenesis.Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma.Pulmonary malignant melanoma with distant metastasis assessed by positron emission tomography-computed tomography.The development and validation of a CT-based radiomics signature for the preoperative discrimination of stage I-II and stage III-IV colorectal cancerNon-small cell lung cancer: quantitative phenotypic analysis of CT images as a potential marker of prognosis.CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas.Quantitative image variables reflect the intratumoral pathologic heterogeneity of lung adenocarcinoma.Combining radiomic features with a miRNA classifier may improve prediction of malignant pathology for pancreatic intraductal papillary mucinous neoplasmsPredicting tumour response.MRI for assessing and predicting response to neoadjuvant treatment in rectal cancer.The role of texture analysis in imaging as an outcome predictor and potential tool in radiotherapy treatment planning.IBEX: an open infrastructure software platform to facilitate collaborative work in radiomics.Defining the biological basis of radiomic phenotypes in lung cancer.Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.Gastric cancer: texture analysis from multidetector computed tomography as a potential preoperative prognostic biomarker.
P2860
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P2860
Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh
2012年學術文章
@zh-hant
name
Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
@en
type
label
Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
@en
prefLabel
Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
@en
P2093
P356
P1433
P1476
Non-small cell lung cancer: histopathologic correlates for texture parameters at CT.
@en
P2093
Balaji Ganeshan
Henry C Mandeville
Kenneth A Miles
Peter J Hoskin
Quan Sing Ng
P304
P356
10.1148/RADIOL.12112428
P407
P577
2012-11-20T00:00:00Z