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Angiomyolipoma

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Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

European radiology 29134348
OBJECTIVE: To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC).
Angiomyolipoma Carcinoma, Renal Cell Diagnosis, Differential Female Humans Kidney Neoplasms Male Middle Aged Reproducibility of Results Retrospective Studies Sensitivity and Specificity Support Vector Machine Tomography, X-Ray Computed
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Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast-enhanced CT images with texture image patches and hand-crafted feature concatenation.

Medical physics 29474742
PURPOSE: To develop an automatic deep feature classification (DFC) method for distinguishing benign angiomyolipoma without visible fat (AMLwvf) from malignant clear cell renal cell carcinoma (ccRCC) from abdominal contrast-enhanced computer tomograph...
Angiomyolipoma Carcinoma, Renal Cell Contrast Media Diagnosis, Differential Humans Image Processing, Computer-Assisted Kidney Neoplasms Machine Learning Radiography, Abdominal Sensitivity and Specificity Tomography, X-Ray Computed
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Differentiation of renal angiomyolipoma without visible fat from renal cell carcinoma by machine learning based on whole-tumor computed tomography texture features.

Acta radiologica (Stockholm, Sweden : 1987) 30799634
Angiomyolipoma Carcinoma, Renal Cell Diagnosis, Differential Female Humans Image Interpretation, Computer-Assisted Kidney Kidney Neoplasms Machine Learning Male Middle Aged Reproducibility of Results Retrospective Studies Tomography, X-Ray Computed
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Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

Ultrasound in medicine & biology 31133445
The question of whether ultrasound point shear wave elastography can differentiate renal cell carcinoma (RCC) from angiomyolipoma (AML) is controversial. This study prospectively enrolled 51 patients with 52 renal tumors (42 RCCs, 10 AMLs). We obtain...
Adolescent Adult Aged Aged, 80 and over Angiomyolipoma Carcinoma, Renal Cell Diagnosis, Differential Elasticity Imaging Techniques Female Humans Image Interpretation, Computer-Assisted Kidney Kidney Neoplasms Machine Learning Male Middle Aged Prospective Studies Reproducibility of Results Sensitivity and Specificity Young Adult
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