Entry 16
Abstract
Nanotechnology and image processing are two of the most rapidly growing
interdisciplinary research fields. Gold nanoparticles have recently appeared
in novel applications ranging from photovoltaics , to protein
sensing , and even to boiling water . Likewise, fascinating
applications of image processing, for example in areas like computer vision,
ensure vested interest from academic and commercial organizations for the
foreseeable future.
High-resolution microscopy (HRM) is the keystone between nanotech and image
processing. This is not surprising, since small variations in nanoparticle
morphology, both at the individual particle and ensemble scale, drastically
affect the macroscopic properties of the composite. One would expect to find a
considerable body of knowledge and software geared towards HRM nanomaterial
processing; however, this is not the case. Despite similar requirements in
image acquisition and processing, fields like cell profiling vastly
overshadow nanotech. HRM in terms of knowledge base and dedicated software.
Using scientific Python, especially Scikit-image, we have begun addressing this
disparity.
We sought to create a guide for nanomaterial image processing, but didn’t want
to make biased assessments based on our experimental images. Using
Scikit-image and a complementary particle analysis library, PyParty, we set
out to build artificial electron microscope images. We could then compare the
performance of preprocessing and segmentation algorithms in the context of
nanoscience, and begin to assemble targeted workflows. The chosen image
features particles of varying multiplicity, brightness and orientation,
patterned over a shadowed background. Realistic particle edges were obtained
with Gaussian smoothing, and normal noise was generated in Numpy. We have
already successfully used these images in several endeavors, from assessing the
performance of new supervised object classification tools , to building
predictive models for nanoparticle-ligand binding on rough thin films. These
images are available for public use, and we hope they will be repurposed many
times.