-
1
-
-
84930180519
-
Imaging the solitary pulmonary nodule
-
Alpert, J. B., Lowry, C. M. & Ko, J. P. Imaging the solitary pulmonary nodule. Clin Chest Med. 36, 161-178, vii (2015).
-
(2015)
Clin Chest Med.
, vol.36
, Issue.161-178
, pp. 7
-
-
Alpert, J.B.1
Lowry, C.M.2
Ko, J.P.3
-
2
-
-
84940823468
-
British Thoracic Society guidelines for the investigation and management of pulmonary nodules
-
Callister, M. E. et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax. 70 Suppl 2, ii1-ii54 (2015).
-
(2015)
Thorax
, vol.70
, pp. ii1-ii54
-
-
Callister, M.E.1
-
3
-
-
84885433266
-
The solitary pulmonary nodule in patients with previous cancer history: Results of surgical treatment
-
Rena, O. et al. The solitary pulmonary nodule in patients with previous cancer history: results of surgical treatment. Eur J Surg Oncol. 39, 1248-1253 (2013).
-
(2013)
Eur J Surg Oncol.
, vol.39
, pp. 1248-1253
-
-
Rena, O.1
-
4
-
-
77449111787
-
Solitary pulmonary nodule: Diagnosis criteria and management
-
Jimborean, G., Ianosi, E. S., Comes, A., Budin, C. & Preda, D. Solitary pulmonary nodule: diagnosis criteria and management. Pneumologia. 58, 211-218 (2009).
-
(2009)
Pneumologia.
, vol.58
, pp. 211-218
-
-
Jimborean, G.1
Ianosi, E.S.2
Comes, A.3
Budin, C.4
Preda, D.5
-
5
-
-
0033825783
-
Evaluation and management of the solitary pulmonary nodule
-
Ost, D. & Fein, A. Evaluation and management of the solitary pulmonary nodule. Am J Respir Crit Care Med. 162, 782-787 (2000).
-
(2000)
Am J Respir Crit Care Med.
, vol.162
, pp. 782-787
-
-
Ost, D.1
Fein, A.2
-
6
-
-
84920837701
-
Cancer statistics 2015
-
Siegel, R. L., Miller, K. D. & Jemal, A. Cancer statistics, 2015. CA Cancer J Clin. 65, 5-29 (2015).
-
(2015)
CA Cancer J Clin
, vol.65
, pp. 5-29
-
-
Siegel, R.L.1
Miller, K.D.2
Jemal, A.3
-
7
-
-
78049485263
-
Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008
-
Ferlay, J. et al. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 127, 2893-2917 (2010).
-
(2010)
Int J Cancer.
, vol.127
, pp. 2893-2917
-
-
Ferlay, J.1
-
8
-
-
84933671890
-
A modified model for preoperatively predicting malignancy of solitary pulmonary nodules: An Asia cohort study
-
Zheng, B. et al. A Modified Model for Preoperatively Predicting Malignancy of Solitary Pulmonary Nodules: An Asia Cohort Study. Ann Thorac Surg. 100, 288-294 (2015).
-
(2015)
Ann Thorac Surg.
, vol.100
, pp. 288-294
-
-
Zheng, B.1
-
9
-
-
84855524040
-
Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: Prognostic factors from CT findings
-
Ikehara, M. et al. Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: prognostic factors from CT findings. Eur J Radiol. 81, 189-194 (2012).
-
(2012)
Eur J Radiol.
, vol.81
, pp. 189-194
-
-
Ikehara, M.1
-
10
-
-
54049111428
-
Computer-aided diagnosis in lung nodule assessment
-
Goldin, J. G., Brown, M. S. & Petkovska, I. Computer-aided diagnosis in lung nodule assessment. Journal of thoracic imaging. 23, 97-104 (2008).
-
(2008)
Journal of Thoracic Imaging.
, vol.23
, pp. 97-104
-
-
Goldin, J.G.1
Brown, M.S.2
Petkovska, I.3
-
11
-
-
34047216935
-
Accuracy of PET/CT in characterization of solitary pulmonary lesions
-
Kim, S. K. et al. Accuracy of PET/CT in characterization of solitary pulmonary lesions. J Nucl Med. 48, 214-220 (2007).
-
(2007)
J Nucl Med.
, vol.48
, pp. 214-220
-
-
Kim, S.K.1
-
12
-
-
26944492713
-
Morphological characteristics of malignant solitary pulmonary nodules
-
Paslawski, M., Krzyzanowski, K., Zlomaniec, J. & Gwizdak, J. Morphological characteristics of malignant solitary pulmonary nodules. Ann Univ Mariae Curie Sklodowska Med. 59, 6-13 (2004).
-
(2004)
Ann Univ Mariae Curie Sklodowska Med.
, vol.59
, pp. 6-13
-
-
Paslawski, M.1
Krzyzanowski, K.2
Zlomaniec, J.3
Gwizdak, J.4
-
13
-
-
84955604605
-
Radiomics: Images Are More than Pictures
-
Gillies, R. J., Kinahan, P. E. & Hricak, H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 278, 563-577 (2016).
-
(2016)
They Are Data. Radiology
, vol.278
, pp. 563-577
-
-
Gillies, R.J.1
Kinahan, P.E.2
Hricak, H.3
-
14
-
-
84901946941
-
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
-
Aerts, H. J. et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nature communications 5, 4006 (2014).
-
(2014)
Nature Communications
, vol.5
, pp. 4006
-
-
Aerts, H.J.1
-
15
-
-
84893431926
-
Behind the numbers: Decoding molecular phenotypes with radiogenomics-guiding principles and technical considerations
-
Kuo, M. D. & Jamshidi, N. Behind the numbers: Decoding molecular phenotypes with radiogenomics-guiding principles and technical considerations. Radiology 270, 320-325 (2014).
-
(2014)
Radiology
, vol.270
, pp. 320-325
-
-
Kuo, M.D.1
Jamshidi, N.2
-
16
-
-
84857037061
-
Radiomics: Extracting more information from medical images using advanced feature analysis
-
Lambin, P. et al. Radiomics: extracting more information from medical images using advanced feature analysis. European journal of cancer 48, 441-446 (2012).
-
(2012)
European Journal of Cancer
, vol.48
, pp. 441-446
-
-
Lambin, P.1
-
17
-
-
84983293947
-
CT texture analysis can help differentiate between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer
-
Andersen, M. B. et al. CT texture analysis can help differentiate between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer. Acta Radiol. 0(0), 1-8 (2015).
-
(2015)
Acta Radiol.
, pp. 1-8
-
-
Andersen, M.B.1
-
18
-
-
84920858276
-
Quantitative CT texture and shape analysis: Can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer?
-
Bayanati, H. et al. Quantitative CT texture and shape analysis: can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer? Eur Radiol. 25, 480-487 (2015).
-
(2015)
Eur Radiol.
, vol.25
, pp. 480-487
-
-
Bayanati, H.1
-
19
-
-
84943774122
-
Measuring computed tomography scanner variability of radiomics features
-
Mackin, D. et al. Measuring Computed Tomography Scanner Variability of Radiomics Features. Invest Radiol. 50, 757-765 (2015).
-
(2015)
Invest Radiol.
, vol.50
, pp. 757-765
-
-
Mackin, D.1
-
20
-
-
84857973864
-
Optical differentiation between malignant and benign lymphadenopathy by grey scale texture analysis of endobronchial ultrasound convex probe images
-
Nguyen, P. et al. Optical differentiation between malignant and benign lymphadenopathy by grey scale texture analysis of endobronchial ultrasound convex probe images. Chest. 141, 709-715 (2012).
-
(2012)
Chest.
, vol.141
, pp. 709-715
-
-
Nguyen, P.1
-
21
-
-
84890482499
-
Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters
-
Wang, J. J. et al. Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters. Asian Pac J Cancer Prev. 14, 6019-6023 (2013).
-
(2013)
Asian Pac J Cancer Prev.
, vol.14
, pp. 6019-6023
-
-
Wang, J.J.1
-
22
-
-
84938850455
-
Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer
-
Parmar, C. et al. Radiomic feature clusters and prognostic signatures specific for Lung and Head & Neck cancer. Sci Rep. 5, 11044 (2015).
-
(2015)
Sci Rep.
, vol.5
, pp. 11044
-
-
Parmar, C.1
-
23
-
-
84955724184
-
External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma
-
Leijenaar, R. T. et al. External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma. Acta Oncol. 54, 1423-1429 (2015).
-
(2015)
Acta Oncol.
, vol.54
, pp. 1423-1429
-
-
Leijenaar, R.T.1
-
24
-
-
84867139157
-
Radiomics: The process and the challenges
-
Kumar, V. et al. Radiomics: the process and the challenges. Magn Reson Imaging. 30, 1234-1248 (2012).
-
(2012)
Magn Reson Imaging.
, vol.30
, pp. 1234-1248
-
-
Kumar, V.1
-
25
-
-
48249153186
-
Intraclass correlations: Uses in assessing rater reliability
-
Shrout, P. E. & Fleiss, J. L. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 86, 420-428 (1979).
-
(1979)
Psychol Bull.
, vol.86
, pp. 420-428
-
-
Shrout, P.E.1
Fleiss, J.L.2
-
26
-
-
77950537175
-
Regularization paths for generalized linear models via coordinate descent
-
Friedman, J., Hastie, T. & Tibshirani, R. Regularization Paths for Generalized Linear Models via Coordinate Descent. J Stat Softw. 33, 1-22 (2010).
-
(2010)
J Stat Softw.
, vol.33
, pp. 1-22
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
27
-
-
0023710206
-
Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach
-
DeLong, E. R., DeLong, D. M. & Clarke-Pearson, D. L. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 44, 837-845 (1988).
-
(1988)
Biometrics.
, Issue.44
, pp. 837-845
-
-
DeLong, E.R.1
DeLong, D.M.2
Clarke-Pearson, D.L.3
-
28
-
-
38849091997
-
Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond
-
discussion 207-112
-
Pencina, M. J., D'Agostino, R. B. Sr., D'Agostino, R. B. Jr. & Vasan, R. S. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 27, 157-172; discussion 207-112 (2008).
-
(2008)
Stat Med.
, vol.27
, pp. 157-172
-
-
Pencina, M.J.1
D'Agostino, R.B.2
D'Agostino, R.B.3
Vasan, R.S.4
-
29
-
-
78649477601
-
Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers
-
Pencina, M. J., DAgostino, R. B. Sr. & Steyerberg, E. W. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 30, 11-21 (2011).
-
(2011)
Stat Med.
, vol.30
, pp. 11-21
-
-
Pencina, M.J.1
D'Agostino, R.B.2
Steyerberg, E.W.3
-
30
-
-
84893257511
-
Net reclassification improvement: Computation, interpretation, and controversies: A literature review and clinicians guide
-
Leening, M. J., Vedder, M. M., Witteman, J. C., Pencina, M. J. & Steyerberg, E. W. Net reclassification improvement: computation, interpretation, and controversies: a literature review and clinicians guide. Ann Intern Med. 160, 122-131 (2014).
-
(2014)
Ann Intern Med.
, vol.160
, pp. 122-131
-
-
Leening, M.J.1
Vedder, M.M.2
Witteman, J.C.3
Pencina, M.J.4
Steyerberg, E.W.5
-
31
-
-
84904248018
-
Robust Radiomics feature quantification using semiautomatic volumetric segmentation
-
Parmar, C. et al. Robust Radiomics feature quantification using semiautomatic volumetric segmentation. Plos One. 9, e102107 (2014).
-
(2014)
Plos One.
, vol.9
, pp. e102107
-
-
Parmar, C.1
-
32
-
-
84884562832
-
Stability of FDG-PET Radiomics features: An integrated analysis of test-retest and inter-observer variability
-
Leijenaar, R. T. et al. Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability. Acta Oncol. 52, 1391-1397 (2013).
-
(2013)
Acta Oncol.
, vol.52
, pp. 1391-1397
-
-
Leijenaar, R.T.1
-
33
-
-
84890056425
-
High quality machine-robust image features: Identification in nonsmall cell lung cancer computed tomography images
-
Hunter, L. A. et al. High quality machine-robust image features: identification in nonsmall cell lung cancer computed tomography images. Med Phys. 40, 121916 (2013).
-
(2013)
Med Phys.
, vol.40
, pp. 121916
-
-
Hunter, L.A.1
-
34
-
-
84876196444
-
Quantifying tumour heterogeneity with CT
-
Ganeshan, B. & Miles, K. A. Quantifying tumour heterogeneity with CT. Cancer Imaging. 13, 140-149 (2013).
-
(2013)
Cancer Imaging.
, vol.13
, pp. 140-149
-
-
Ganeshan, B.1
Miles, K.A.2
-
35
-
-
63649084909
-
Texture analysis in non-contrast enhanced CT: Impact of malignancy on texture in apparently disease-free areas of the liver
-
Ganeshan, B., Miles, K. A., Young, R. C. & Chatwin, C. R. Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver. Eur J Radiol. 70, 101-110 (2009).
-
(2009)
Eur J Radiol.
, vol.70
, pp. 101-110
-
-
Ganeshan, B.1
Miles, K.A.2
Young, R.C.3
Chatwin, C.R.4
-
36
-
-
80053066718
-
Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker
-
Goh, V. et al. Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker. Radiology. 261, 165-171 (2011).
-
(2011)
Radiology.
, vol.261
, pp. 165-171
-
-
Goh, V.1
-
37
-
-
84902489272
-
Exploring Variability in CT Characterization of Tumors: A Preliminary Phantom Study
-
Zhao, B., Tan, Y., Tsai, W. Y., Schwartz, L. H. & Lu, L. Exploring Variability in CT Characterization of Tumors: A Preliminary Phantom Study. Transl Oncol. 7, 88-93 (2014).
-
(2014)
Transl Oncol.
, vol.7
, pp. 88-93
-
-
Zhao, B.1
Tan, Y.2
Tsai, W.Y.3
Schwartz, L.H.4
Lu, L.5
-
38
-
-
84872009099
-
Assessing the effect of CT slice interval on unidimensional, bidimensional and volumetric measurements of solid tumours
-
Tan, Y. et al. Assessing the effect of CT slice interval on unidimensional, bidimensional and volumetric measurements of solid tumours. Cancer Imaging. 12, 497-505 (2012).
-
(2012)
Cancer Imaging.
, vol.12
, pp. 497-505
-
-
Tan, Y.1
-
39
-
-
79251500311
-
Hybrid convolution kernel: Optimized CT of the head, neck, and spine
-
Weiss, K. L. et al. Hybrid convolution kernel: optimized CT of the head, neck, and spine. AJR Am J Roentgenol. 196, 403-406 (2011).
-
(2011)
AJR Am J Roentgenol.
, vol.196
, pp. 403-406
-
-
Weiss, K.L.1
-
40
-
-
84923923813
-
Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD statement
-
Collins, G. S., Reitsma, J. B., Altman, D. G. & Moons, K. G. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med. 162, 55-63 (2015).
-
(2015)
Ann Intern Med.
, vol.162
, pp. 55-63
-
-
Collins, G.S.1
Reitsma, J.B.2
Altman, D.G.3
Moons, K.G.4
|