CellProfiler uses scikit-image for computer vision operations (i.e. image processing and analysis) and scikit-image uses NumPy and SciPy for algebraic and optimization operations, so CellProfiler won’t support CUDA (or OpenCL) until there’s downstream support (i.e. NumPy and SciPy support them).
If you’re adventurous, NVIDIA recently released cuBLAS, so it might be possible to link NumPy and cuBLAS and run CellProfiler with your cuBLAS-linked NumPy and receive some performance advantage. However, this is completely theoretical.
Alternatively, you could fork CellProfiler and replace scikit-image calls with equivalent or similar calls from OpenCV’s CUDA library. It’d require some work, but you could potentially receive dramatic speedups (e.g. OpenCV claims CUDA functions have a 30x speedup for image processing functions).