Abstract: Various embodiments of the invention relate to a system 100 and method 200 for image analysis. In particular, various embodiments of the invention relate to a system 100 and method 200 for extracting low-intensity features from an image data set comprising data corresponding to a sequence of original image frames 502, 504, 506, 508, 510. One such method 200 comprises determining 202 a plurality of principal components PC1, PC2, PC3, PC4, PC5, PC6 from the image data set corresponding to the original image frames, applying 204 a principal component analysis (PCA) filter to the plurality of principal components PC1, components PC2, PC3, PC4, PC5, PC6 to determine a filtered data set by discarding at least one principal component PC1 from the plurality of principal components PC1, PC2, PC3, PC4, PC5, PC6, and transforming 206 the filtered data set to create a plurality of filtered image frames 402, 404, 406, 408, 410 having enhanced low-intensity features.

Abstract: In a method and system for outlining a region of interest in a Positron Emission Tomography (PET) scan study, a processor may, based on application of Masked Volume Wise Principal Component Analysis (MVW-PCA) to a plurality of scan images, generate a PC2 image showing kinetic behavior of a particular part of a subject, in particular, the grey matter of the cerebellar cortex of the subject, and may outline, in the PC2 image, a region of the PC2 image having highest pixel intensity values of the PC2 image or of a portion thereof as a region of interest, and, in particular, as a reference region. The processor may generate a PC3 image showing kinetic behavior of a different part of the subject, in particular, blood vessels of the subject, import the outline into the PC3 image to determine the correctness of the outline, and modify the outline if it is incorrect.