1. An atlas-free magnetic resonance imaging method configured for imaging at least one part of a brain, the method comprising the steps of: using a magnetic resonance imaging sequence configured for acquiring two image volumes, respectively a first image volume and a second image volume, of the part of the brain at mutually different inversion times within a single acquisition, wherein the magnetic resonance imaging sequence is a Magnetization-Prepared 2 Rapid Gradient-Echoes sequence with a first echo time TE1 and a second echo time TE2 for each inversion contrast; using a Dixon method for acquiring a fat-water separated image of the part, so that the fat and water component are in-phase and opposed-phase; using magnetic resonance imaging and the magnetic resonance imaging sequence for acquiring for each inversion time TI1 and TI2 the two image volumes, respectively the first image volume and the second image volume at the first echo time, and the first image volume and the second image volume at the second echo time; for each echo time, combining the two image volumes to form a “uniform” image, respectively a first uniform image at the first echo time and a second uniform image at the second echo time; applying a fat-water separation method to the first image volume of the first and second inversion time TI1 and TI2 for obtaining a first fat-water separated image and/or applying a fat-water separation method to the second image volume of the first and second inversion time TI1 and TI2 for obtaining a second fat-water separated image; feeding a multichannel image segmentation algorithm with at least the following input images: a final uniform image resulting from a combination of the uniform images; a final fat-water separated image resulting from a combination of the fat-water separated images; a final second image volume resulting from a combination of the second image volumes; wherein the multichannel image segmentation algorithm uses a Markov random field model for segmenting the part into multiple classes of cranial tissues from data arising from the input images; and outputting a segmented image of the part.