Systems and methods for the automated detection of cerebral microbleeds using 3T MRI

A system for cerebral microbleed detection, the system comprising:

• a computing device comprising a processor, a memory, input/output circuitry, and a data store;
• a preprocessor module configured to acquire magnetic resonance imaging (MRI) image data, the MRI image data comprising T1-weighted MRI image data and acquired T2*-weighted image data;
• the preprocessor module further configured to extract extracted T2*-weighted image data from the acquired T2*-weighted image data, the extracted T2*-weighted image data corresponding to gradient echo (GRE) image data or susceptibility-weighted imaging (SWI) image data;
• the preprocessor module further configured to resample the extracted T2*-weighted image data to a relatively higher resolution to yield resampled image data, the resampled image data comprising a plurality of slices;
• a detection module configured to identify each potential microbleed location in each slice of the resampled image data based, at least in part, on a respective intensity of each of a plurality of resampled image pixels, each potential microbleed location corresponding to a potential region of interest (ROI) and having a circular or ellipsoidal shape to within a shape tolerance;
• the detection module further configured to reduce a number of potential ROIs based, at least in part on at least one reduction criterion to yield a reduced number of potential two-dimensional (2D) ROIs;
• the detection module further configured to merge the reduced number of 2D ROIs into at least one merged potential three dimensional (3D) ROI, the merging performed between a plurality of adjacent slices;
• the detection module further configured to define a standardized potential 3D ROI for each merged potential 3D ROI, each standardized potential 3D ROI having a respective 3D center and a surrounding neighborhood having a common size;
• a 3D geometric filtering module configured to remove each potential false positive 3D ROI from the at least one standardized potential 3D ROI based, at least in part, on at least one 3D ROI characteristic of each standardized potential 3D ROI, to yield a number of final potential 3D ROIs;
• and
• a final module configured to store each of the final potential 3D ROIs comprising a location and a volume, associated with the extracted T2*-weighted image data, for review by a trained rater.

A computer readable storage device having stored thereon instructions that when executed by one or more processors result in the following operations comprising:

• acquiring magnetic resonance imaging (MRI) image data, the MRI image data comprising T1-weighted MRI image data and acquired T2*-weighted image data;
• extracting extracted T2*-weighted image data from the acquired T2*-weighted image data, the extracted T2*-weighted image data corresponding to gradient echo (GRE) image data or susceptibility-weighted imaging (SWI) image data;
• resampling the extracted T2*-weighted image data to a relatively higher resolution to yield resampled image data, the resampled image data comprising a plurality of slices;
• identifying each potential microbleed location in each slice of the resampled image data based, at least in part, on a respective intensity of each of a plurality of resampled image pixels, each potential microbleed location corresponding to a potential region of interest (ROI) and having a circular or ellipsoidal shape to within a shape tolerance;
• reducing a number of potential ROIs based, at least in part on at least one reduction criterion to yield a reduced number of potential two-dimensional (2D) ROIs;
• merging the reduced number of 2D ROIs into at least one merged potential three dimensional (3D) ROI, the merging performed between a plurality of adjacent slices;
• defining a standardized potential 3D ROI for each merged potential 3D ROI, each standardized potential 3D ROI having a respective 3D center and a surrounding neighborhood having a common size;
• removing each potential false positive 3D ROI from the at least one standardized potential 3D ROI based, at least in part, on at least one 3D ROI characteristic of each standardized potential 3D ROI, to yield a number of final potential 3D ROIs;
• and
• storing each of the final potential 3D ROIs comprising a location and a volume, associated with the extracted T2*-weighted image data, for review by a trained rater.