Although a variety of imaging modalities are used or currently being investigated for patients with brain tumors including brain metastases, clinical image interpretation to date uses only a fraction of the underlying complex, high-dimensional digital information from routinely acquired imaging data. The growing availability of high-performance computing allows the extraction of quantitative imaging features from medical images that are usually beyond human perception. Using machine learning techniques and advanced statistical methods, subsets of such imaging features are used to generate mathematical models that represent characteristic signatures related to the underlying tumor biology and might be helpful for the assessment of prognosis ...
Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortali...
International audienceBrain metastases (BM) from extracranial cancer are associated with significant...
Background and Objective: Specific treatment for each patient based on their clinical data is one of...
Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET...
Radiomics describes a broad set of computational methods that extract quantitative features from rad...
IntroductionBrain metastases in patients with extracranial cancer are typically associated with incr...
BackgroundMagnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the ...
Radiomics is a technique that uses high-throughput computing to extract quantitative features from t...
Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients w...
Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients w...
Brain metastasis (BM) is a major cause of cancer patient morbidity. Clinical magnetic resonance imag...
The development of clinical trials has led to substantial improvements in the prevention and treatme...
Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortali...
Medical imaging gives valuable information for diagnosis and treatment planning of cancer patients. ...
Recent advances in medical image analysis have been made to improve our understanding of how disease...
Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortali...
International audienceBrain metastases (BM) from extracranial cancer are associated with significant...
Background and Objective: Specific treatment for each patient based on their clinical data is one of...
Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET...
Radiomics describes a broad set of computational methods that extract quantitative features from rad...
IntroductionBrain metastases in patients with extracranial cancer are typically associated with incr...
BackgroundMagnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the ...
Radiomics is a technique that uses high-throughput computing to extract quantitative features from t...
Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients w...
Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients w...
Brain metastasis (BM) is a major cause of cancer patient morbidity. Clinical magnetic resonance imag...
The development of clinical trials has led to substantial improvements in the prevention and treatme...
Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortali...
Medical imaging gives valuable information for diagnosis and treatment planning of cancer patients. ...
Recent advances in medical image analysis have been made to improve our understanding of how disease...
Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortali...
International audienceBrain metastases (BM) from extracranial cancer are associated with significant...
Background and Objective: Specific treatment for each patient based on their clinical data is one of...