![]() ITK's Python bindings (SimpleITK) was not pippable or easily usable yet, and I found working with image data as numpy arrays far preferable and faster than using ITK as a library in custom C++ programs which I'd need to compile and recompile as an analysis developed. This project started out at a time when I was analyzing lots of Gate image outputs. SimpleITK write also only seems to produce usable dicoms files when updating an existing image, not when creating a new one from scratch. If it would, it would require SimpleITK, primarily because pydicom does not support dicom image write. This component is governed by its own license.ĭicom write is not supported right now. For NKI decompression I supply a 64bit Linux and Windows lib, if you need support for other platforms you can compile the function in medimage/nki_decomp yourself. Of particular interest perhaps are the DVH analysis function, and the distance to agreement calculation. Included are some basic mathematical operations, some masking functions and crop and resampling functions. Slicing, projections, mathematical operations, masking, stuff like that is very easy with numpy, so you can easily extend things to what you need. imdata member) such that you can easily work with images in these data formats. ![]() The image class is a thin wrapper around typed numpy array objects (the. ![]() XDR reading includes NKI compressed images (useful to work with your Elekta images). This library supports r/w MetaImage (MHD,ITK), r/w AVSField (.xdr) and read Dicom images.
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