Patent ID: 11971466
Assignee: ESAOTE S.P.A.
Field: Medical technology (Instruments)
Classification: CPC G  A | IPC A  G

Claim 3:
4. A method for separate acquisition and output of diagnostic images in nuclear magnetic resonance imaging based on signals from water and fat, which method comprises:
a) defining at least a slice of an image that passes through a body, or an area of a body, under examination with a pre-established relative orientation:
b) acquiring for at least said slice or for at least a part of all said slices when there are more than one slice, at least an anatomical image in nuclear magnetic resonance along said slice;
(c) performing, for at least said slice or for at least part of all of said slices when there are more than one, and for each pixel or voxel of the nuclear magnetic resonance image acquired along said slice, a separation of signal components corresponding to an intensity of said pixel or voxel resulting from water within the body under examination from those signal components resulting from fat tissues in said body under examination;
(d) generating for at least said slice, or for at least part of all of said slices when there are more than one, an image called water-only which is generated on the basis of signal components of MRI signals resulting from water-only separated in step (c);
(e) generating for at least a slice, or for at least part of all of said slices when there are more than one, an image called fat-only which is generated on the basis of signal components of the MRI signals resulting from fat-only separated in step (c);
(f) sorting images related to any single slice in a sequence that for each slice provides firstly for said anatomical image(s) and afterward said water-only image(s) followed by said fat-only image(s);
g) sorting images related to any single slice according by position order of said slices when there are more than one, and wherein
h) the separation of signal components corresponding to intensity of said pixel or voxel resulting from water within the body under examination from those signal components resulting from fat tissues in said body under examination of step c) being performed by a machine learning algorithm that uses automatic learning to configure the machine learning algorithm process based on feedback mechanisms involving training and testing processes with image data; and
prior to step (c) selecting a descriptive parameter of each pixel or voxel of an image, which is a combination of descriptive parameters of one or more boundary pixels or voxels of said parameter weighed according to the distance from said pixel or voxel.