In this paper we report the set-up and results of the Multimodal Brain Tumor Image
Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and …

Half a century ago, the term “computer-aided diagnosis”(CAD) was introduced in the
scientific literature. Pulmonary imaging, with chest radiography and computed tomography …

International challenges have become the standard for validation of biomedical image
analysis methods. Given their scientific impact, it is surprising that a critical analysis of …

The purpose of this statement is to describe and define the phenotypic abnormalities that
can be identified on visual and quantitative evaluation of computed tomographic (CT) …

Automatic whole-brain extraction from magnetic resonance images (MRI), also known as
skull stripping, is a key component in most neuroimage pipelines. As the first element in the …

Segmentation of anatomical structures, from modalities like computed tomography (CT),
magnetic resonance imaging (MRI) and ultrasound, is a key enabling technology for medical …

Computed tomography (CT) is an effective med-ical imaging modality, widely used in the
field of clinical medicine for the diagnosis of various pathologies. Advances in Multidetector …

Variations in the shape and appearance of anatomical structures in medical images are
often relevant radiological signs of disease. Automatic tools can help automate parts of this …

Open international challenges are becoming the de facto standard for assessing computer
vision and image analysis algorithms. In recent years, new methods have extended the …

Deep learning is a genre of machine learning that allows computational models to learn
representations of data with multiple levels of abstraction using numerous processing layers …