Related references
Note: Only part of the references are listed.Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma
Zhichao Feng et al.
EUROPEAN RADIOLOGY (2018)
Renal angiomyolipoma without visible fat: Can we make the diagnosis using CT and MRI?
Robert S. Lim et al.
EUROPEAN RADIOLOGY (2018)
2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution
Monika Beresova et al.
MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE (2018)
Morphologic analysis with computed tomography may help differentiate fat-poor angiomyolipoma from renal cell carcinoma: a retrospective study with 602 patients
Yong Hee Kim et al.
ABDOMINAL RADIOLOGY (2018)
Subjective and objective heterogeneity scores for differentiating small renal masses using contrast-enhanced CT
Shuai Leng et al.
ABDOMINAL RADIOLOGY (2017)
Differentiation of fat-poor angiomyolipoma from clear cell renal cell carcinoma in contrast-enhanced MDCT images using quantitative feature classification
Han Sang Lee et al.
MEDICAL PHYSICS (2017)
Texture analysis as a radiomic marker for differentiating renal tumors
HeiShun Yu et al.
ABDOMINAL RADIOLOGY (2017)
Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer
Yucheng Zhang et al.
SCIENTIFIC REPORTS (2017)
Computational Radiomics System to Decode the Radiographic Phenotype
Joost J. M. van Griethuysen et al.
CANCER RESEARCH (2017)
Angiomyolipoma (AML) without visible fat: Ultrasound, CT and MR imaging features with pathological correlation
Shaheed W. Hakim et al.
EUROPEAN RADIOLOGY (2016)
Unenhanced CT and MRI Parameters That Can Be Used to Reliably Predict Fat-Invisible Angiomyolipoma
Chae Jin Jeong et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2016)
Lipid-poor renal angiomyolipoma: Differentiation from clear cell renal cell carcinoma using wash-in and washout characteristics on contrast-enhanced computed tomography
Pingkun Xie et al.
ONCOLOGY LETTERS (2016)
Angiomyolipoma with Minimal Fat: Differentiation From Clear Cell Renal Cell Carcinoma and Papillary Renal Cell Carcinoma by Texture Analysis on CT Images
Lifen Yan et al.
ACADEMIC RADIOLOGY (2015)
Diagnosis of Sarcomatoid Renal Cell Carcinoma With CT: Evaluation by Qualitative Imaging Features and Texture Analysis
Nicola Schieda et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2015)
Small (< 4 cm) Renal Masses: Differentiation of Angiomyolipoma Without Visible Fat From Renal Cell Carcinoma Using Unenhanced and Contrast-Enhanced CT
Naoki Takahashi et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2015)
Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images?
Taryn Hodgdon et al.
RADIOLOGY (2015)
Renal Angiomyolipoma: Preoperative Identification of Atypical Fat-Poor AML
Crystal Farrell et al.
CURRENT UROLOGY REPORTS (2015)
Renal angiomyolipoma: a radiological classification and update on recent developments in diagnosis and management
Masahiro Jinzaki et al.
ABDOMINAL IMAGING (2014)
CT Texture Analysis of Renal Masses: Pilot Study Using Random Forest Classification for Prediction of Pathology
Siva P. Raman et al.
ACADEMIC RADIOLOGY (2014)
Qualitative and Quantitative MDCT Features for Differentiating Clear Cell Renal Cell Carcinoma From Other Solid Renal Cortical Masses
Stephanie A. Lee-Felker et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2014)
Are There Useful CT Features to Differentiate Renal Cell Carcinoma From Lipid-Poor Renal Angiomyolipoma?
Ching-Wei Yang et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2013)
Angiomyolipoma with minimal fat: Differentiation from papillary renal cell carcinoma by helical CT
Y. -Y. Zhang et al.
CLINICAL RADIOLOGY (2013)
Assessment of tumor heterogeneity by CT texture analysis: Can the largest cross-sectional area be used as an alternative to whole tumor analysis?
Francesca Ng et al.
EUROPEAN JOURNAL OF RADIOLOGY (2013)
Usefulness of the Ice-Cream Cone Pattern in Computed Tomography for Prediction of Angiomyolipoma in Patients With a Small Renal Mass
Kwang Ho Kim et al.
KOREAN JOURNAL OF UROLOGY (2013)
Feature Selection with the Boruta Package
Miron B. Kursa et al.
JOURNAL OF STATISTICAL SOFTWARE (2010)
Incidence of benign pathologic lesions at partial nephrectomy for presumed RCC renal masses: Japanese dual-center experience with 176 consecutive patients
Yasuhisa Fujii et al.
UROLOGY (2008)
Incidence of benign pathologic findings at partial nephrectomy for solitary renal mass presumed to be renal cell carcinoma on preoperative imaging
Alexander Kutikov et al.
UROLOGY (2006)
User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability
Paul A. Yushkevich et al.
NEUROIMAGE (2006)
Angiomyolipoma with minimal fat: Differentiation from renal cell carcinoma at biphasic helical CT
JK Kim et al.
RADIOLOGY (2004)
Gene selection for cancer classification using support vector machines
I Guyon et al.
MACHINE LEARNING (2002)
Share Paper
