International audienceIn this study a MRI-based radiomic method was developed to predict lipomatous soft tissue tumors malignancy. 81 subjects with lipomatous soft tissue tumors whose histology was known and with fat-suppressed T1w contrast enhanced MR images available were retrospectively enrolled to constitute a database. A linear support vector machine was used after learning base dimension reduction to develop the model. Results demonstrate that the evaluation of lipomatous tumor malignancy is feasible with good diagnosis performances using a routinely used MRI acquisition in clinical practice
Purpose: To determine diagnostic performance of MRI radiomics-based machine learning for classificat...
Magnetic resonance imaging (MRI) is generally an efficient tool for establishing the differential di...
Abstract Background To evaluate the diagnostic value of MR imaging for the differentiation of lipoma...
International audienceObjectivesTo develop and validate a MRI-based radiomic method to predict malig...
International audienceIn this study a MRI-based radiomic method was developed to predict lipomatous ...
International audienceIntroduction: Among lipomatous soft tissue tumor, the noninvasive diagnosis be...
International audienceAbstract Objectives Malignancy of lipomatous soft-tissue tumours diagnosis is ...
Background: Well differentiated liposarcoma (WDLPS) can be difficult to distinguish from lipoma. Cur...
Aim: To establish the accuracy of magnetic resonance imaging (MRI) in distinguishing between benign ...
Distinguishing lipoma from liposarcoma is challenging on conventional MRI examination. In case of un...
Lipomatous tumors are among the most common soft tissue tumors (STTs). Magnetic resonance imaging (M...
Purpose/results. We evaluated the diagnostic accuracy of magnetic resonance imaging (MRI) for 46 con...
Abstract The aim of this project on soft tissue tumors, was to evaluate existing imaging methods and...
Purpose: To determine diagnostic performance of MRI radiomics-based machine learning for classificat...
Magnetic resonance imaging (MRI) is generally an efficient tool for establishing the differential di...
Abstract Background To evaluate the diagnostic value of MR imaging for the differentiation of lipoma...
International audienceObjectivesTo develop and validate a MRI-based radiomic method to predict malig...
International audienceIn this study a MRI-based radiomic method was developed to predict lipomatous ...
International audienceIntroduction: Among lipomatous soft tissue tumor, the noninvasive diagnosis be...
International audienceAbstract Objectives Malignancy of lipomatous soft-tissue tumours diagnosis is ...
Background: Well differentiated liposarcoma (WDLPS) can be difficult to distinguish from lipoma. Cur...
Aim: To establish the accuracy of magnetic resonance imaging (MRI) in distinguishing between benign ...
Distinguishing lipoma from liposarcoma is challenging on conventional MRI examination. In case of un...
Lipomatous tumors are among the most common soft tissue tumors (STTs). Magnetic resonance imaging (M...
Purpose/results. We evaluated the diagnostic accuracy of magnetic resonance imaging (MRI) for 46 con...
Abstract The aim of this project on soft tissue tumors, was to evaluate existing imaging methods and...
Purpose: To determine diagnostic performance of MRI radiomics-based machine learning for classificat...
Magnetic resonance imaging (MRI) is generally an efficient tool for establishing the differential di...
Abstract Background To evaluate the diagnostic value of MR imaging for the differentiation of lipoma...