Abstract: A method of classification of image portions corresponding to fecal residues from a tomographic image of a colorectal region, which comprises a plurality of voxels (2) each having a predetermined intensity value and which shows at least one portion of colon (6a, 6b, 6c, 6d) comprising at least one area of tagged material (10). The area of tagged material (10) comprises at least one area of fecal residue (10a) and at least one area of tissue affected by tagging (10b). The image further comprises at least one area of air (8) which comprises an area of pure air (8a) not influenced by the fecal residues. The method comprises the operations of identifying (100), on the basis of a predetermined identification criterion based on the intensity values, above-threshold connected regions comprising connected voxels (2) and identifying, within the above-threshold connected regions, a plurality of connected regions of tagged material comprising voxels (2) representing the area of tagged material (10).

Abstract: A process for the automatic recognition of anomalies in anatomical structures, as well as a processing system and a computer program for implementing the process are described, the process comprising the steps of: acquisition (10) of a plurality of two-dimensional images of at least a portion of a patient's body, which are suitable for forming a three-dimensional representation of at least one anatomical structure under observation, segmentation (20) of a region of interest of the three-dimensional representation, potentially bearing the anomalies, selection (30, 40) of the volume image elements (voxels) of the segmented region that are candidates for belonging to anomalies of the anatomical structure represented, on the basis of predetermined morphological parameters, and classification (70) of the voxels as elements suspected of belonging to anomalies or elements not belonging to anomalies, in which the segmentation (20) takes place by progressive growth of the region of interest by aggregation of voxels

Abstract: A method of classification of image portions corresponding to faecal residues from a tomographic image of a colorectal region, which comprises a plurality of voxels (2) each having a predetermined intensity value and which shows at least one portion of colon (6a, 6b, 6c, 6d) comprising at least one area of tagged material (10). The area of tagged material (10) comprises at least one area of faecal residue (10a) and at least one area of tissue affected by tagging (10b). The image further comprises at least one area of air (8) which comprises an area of pure air (8a) not influenced by the faecal residues. The method comprises the operations of identifying (100), on the basis of a predetermined identification criterion based on the intensity values, above-threshold connected regions comprising connected voxels (2) and identifying, within the above-threshold connected regions, a plurality of connected regions of tagged material comprising voxels (2) representing the area of tagged material (10).

Abstract: A process for the automatic recognition of anomalies in anatomical structures, as well as a processing system and a computer program for implementing the process are described, the process comprising the steps of: acquisition (10) of a plurality of two-dimensional images of at least a portion of a patient's body, which are suitable for forming a three-dimensional representation of at least one anatomical structure under observation, segmentation (20) of a region of interest of the three-dimensional representation, potentially bearing the anomalies, selection (30, 40) of the volume image elements (voxels) of the segmented region that are candidates for belonging to anomalies of the anatomical structure represented, on the basis of predetermined morphological parameters, and classification (70) of the voxels as elements suspected of belonging to anomalies or elements not belonging to anomalies, in which the segmentation (20) takes place by progressive growth of the region of interest by aggregation of voxels