We describe a method turning scatterplot matrix visualizations into malleable graphical objects facilitating interaction and selection of pixelized data elements. The method relies on density estimation techniques [1,2] applied through standard image processing. A 2D scatterplot is considered as an image and is then transformed into nested regions that can be easily selected. Based on Wattenberg and Fisher [3], and as confirmed by our experience, we believe users have a good intuition interpreting and interacting with these multiscale graphical objects. Bio-molecular data serves here as a case study for our methodology. The method was discussed and designed in collaboration with experts in metabonomics and has proven to be useful and complementary to classical statistical methods.