Example #1
0
def recon_with_scatter(json_path, outdir):
    tf.enable_eager_execution()
    if outdir is None:
        outdir = os.path.dirname(os.path.abspath(json_path))
    else:
        outdir = os.path.abspath(outdir)

    mlem_full_without_data = nef.io.json_load(nef.functions.MlemFull,
                                              json_path)
    mlem_obj = nef.io.load_all_data(mlem_full_without_data)
    img = nef.load(nef.Image, outdir + '/recon_image.hdf5')
    if mlem_obj.scatter_corr is not None:
        listmode = mlem_obj.scatter_corr(img, mlem_obj.atten_corr.u_map,
                                         mlem_obj.scanner, outdir)
        listmode = nef.ListmodeCompress(scanner)(listmode)
        mlem_full = nef.MlemFull(mlem_obj.n_iter, mlem_obj.image_config,
                                 mlem_obj.scanner, listmode)
        img = mlem_full()
        nef.save(img, outdir + '/recon_image_scatter.hdf5')
        nef.save(mlem_full_without_data, outdir + '/mlem_full_scatter.hdf5')
        nef.doc_gen(mlem_full_without_data, img, outdir,
                    outdir + '/recon_doc_scatter.md')
        pypandoc.convert_file(outdir + '/recon_doc_scatter.md',
                              'pdf',
                              outputfile=outdir + '/recon_doc_scatter.md' +
                              '.pdf')
        return img
Example #2
0
def recon_full(json_path, outdir):
    tf.enable_eager_execution()
    if outdir is None:
        outdir = os.path.dirname(os.path.abspath(json_path))
    else:
        outdir = os.path.abspath(outdir)

    if not os.path.isdir(outdir):
        os.mkdir(outdir, mode=0o777)

    mlem_full_without_data = nef.io.json_load(nef.functions.MlemFull,
                                              json_path)
    mlem_obj = nef.io.load_all_data(mlem_full_without_data)
    img = mlem_obj()
    from srfnef.corrections.scattering.scatter import scatter_preprocess
    if mlem_obj.scatter_corr is not None:
        scatter_preprocess(mlem_obj.scanner, mlem_obj.listmode, img,
                           mlem_obj.atten_corr.u_map, outdir)
    nef.save(img, outdir + '/recon_image.hdf5')
    # nef.save(mlem_full_without_data, outdir + '/mlem_full.hdf5')
    nef.doc_gen(mlem_full_without_data, img, outdir, outdir + '/recon_doc.md')
    pypandoc.convert_file(outdir + '/recon_doc.md',
                          'pdf',
                          outputfile=outdir + '/recon_doc.md' + '.pdf')
    return img
Example #3
0
def test_full(json_path, outdir, system):
    tf.compat.v1.enable_eager_execution()
    if outdir is None:
        outdir = os.path.dirname(os.path.abspath(json_path))
    else:
        outdir = os.path.abspath(outdir)

    if not os.path.isdir(outdir):
        os.mkdir(outdir, mode=0o777)
    # if system == 'mct':
    mlem_full_without_data = nef.io.json_load(nef.functions.MlemFull,
                                              json_path)
    if system == '8panel':
        with open('/mnt/users/weijie/srfnef/mlem_full.json', 'r') as fin:
            dct = json.load(fin)
        scanner = nef.PetCylindricalScanner.from_dict(dct['scanner'])
    mlem_full_without_data = mlem_full_without_data.update(scanner=scanner)
    mlem_obj = nef.io.load_all_data(mlem_full_without_data)
    opt_atten = [None] if mlem_obj.atten_corr is None else [
        None, mlem_obj.atten_corr
    ]
    opt_psf = [None
               ] if mlem_obj.psf_corr is None else [None, mlem_obj.psf_corr]
    for atten in opt_atten:
        for psf in opt_psf:
            out_append = ''
            if atten is not None:
                out_append += '_atten'
            if psf is not None:
                out_append += '_psf'
            print('*************************************************')
            print(out_append)
            mlem_ = mlem_obj.update(atten_corr=atten,
                                    psf_corr=psf,
                                    scatter_corr=None)
            img = mlem_()
            from srfnef.corrections.scattering.scatter import scatter_preprocess
            scatter_preprocess(mlem_obj.scanner,
                               mlem_obj.listmode,
                               img,
                               mlem_obj.atten_corr.u_map,
                               outdir,
                               out_append=out_append)
            nef.save(img, outdir + f'/recon_image{out_append}.hdf5')
            # with open(json_path, 'r') as fin:
            #     if 'mask' in json.load(fin):
            #         mask_path = json.load(fin)['mask']
            #     else:
            #         mask_path = None
            nef.doc_gen(mlem_full_without_data, img, outdir,
                        outdir + f'/recon_doc{out_append}.md')
            pypandoc.convert_file(outdir + f'/recon_doc{out_append}.md',
                                  'pdf',
                                  outputfile=outdir +
                                  f'/recon_doc{out_append}.md' + '.pdf')

    return img
Example #4
0
def test_with_scatter(json_path, outdir, system):
    tf.enable_eager_execution()
    if outdir is None:
        outdir = os.path.dirname(os.path.abspath(json_path))
    else:
        outdir = os.path.abspath(outdir)

    if not os.path.isdir(outdir):
        os.mkdir(outdir, mode=0o777)

    mlem_full_without_data = nef.io.json_load(nef.functions.MlemFull,
                                              json_path)
    if system == '8panel':
        with open('/mnt/users/weijie/srfnef/mlem_full.json', 'r') as fin:
            dct = json.load(fin)
        scanner = nef.PetCylindricalScanner.from_dict(dct['scanner'])
    mlem_full_without_data = mlem_full_without_data.update(scanner=scanner)
    mlem_obj = nef.io.load_all_data(mlem_full_without_data)
    opt_atten = [None] if mlem_obj.atten_corr is None else [
        None, mlem_obj.atten_corr
    ]
    opt_psf = [None
               ] if mlem_obj.psf_corr is None else [None, mlem_obj.psf_corr]
    for atten in opt_atten:
        for psf in opt_psf:
            out_append = ''
            if atten is not None:
                out_append += '_atten'
            if psf is not None:
                out_append += '_psf'
            print('*************************************************')
            print("scattering")
            img = nef.load(nef.Image,
                           outdir + f'/recon_image{out_append}.hdf5')
            listmode = mlem_obj.scatter_corr(img, mlem_obj.atten_corr.u_map,
                                             mlem_obj.scanner, outdir,
                                             out_append)
            mlem_ = nef.MlemFull(mlem_obj.n_iter, mlem_obj.image_config,
                                 mlem_obj.scanner, listmode)
            img = mlem_()
            out_append += '_scatter'
            print(out_append)
            nef.save(img, outdir + f'/recon_image{out_append}.hdf5')
            nef.doc_gen(mlem_full_without_data, img, outdir,
                        outdir + f'/recon_doc{out_append}.md')
            pypandoc.convert_file(outdir + f'/recon_doc{out_append}.md',
                                  'pdf',
                                  outputfile=outdir +
                                  f'/recon_doc{out_append}.md' + '.pdf')

    return img
Example #5
0
def extract_listmode(path, nsub, outpath, system):
    path = path.replace('sub.0', 'sub.?')
    if system == 'mct':
        listmode = listmode_from_gate_out(path, nef.scanner_mct, int(nsub))
    else:
        raise NotImplementedError

    if not outpath.endswith('.hdf5'):
        outdir = outpath
        if not os.path.isdir(outdir):
            os.mkdir(outdir, mode = 0o777)
        outpath = outdir + '/listmode_trans.hdf5'
    else:
        pass
    nef.save(listmode, outpath)
    print(outpath)
def recon_full(json_path, outdir):
    if outdir is None:
        outdir = os.path.dirname(os.path.abspath(json_path))
    else:
        outdir = os.path.abspath(outdir)

    if not os.path.isdir(outdir):
        os.mkdir(outdir, mode=0o777)

    mlem_full_without_data = nef.io.json_load(
        nef.functions.MlemFullCylindrical, json_path)
    mlem_obj = nef.io.load_all_data(mlem_full_without_data)
    img = mlem_obj()
    nef.save(img, outdir + '/recon_image.hdf5')
    nef.save(mlem_full_without_data, outdir + '/mlem_full.hdf5')
    nef.doc_gen(mlem_full_without_data, img, outdir, outdir + '/recon_doc.md')
    pypandoc.convert_file(outdir + '/recon_doc.md',
                          'pdf',
                          outputfile=outdir + '/recon_doc.md' + '.pdf')
    return img
Example #7
0
def recon_simple(listmode_path, outdir, system, n_iter):
    listmode = nef.load(nef.Listmode, listmode_path)
    if system == 'mct':
        image_config = nef.image_config_mct
        scanner = nef.scanner_mct
    else:
        raise NotImplementedError
    mlem_full = nef.MlemFull(n_iter, image_config, scanner, listmode)
    mlem_full_without_data = mlem_full.update(listmode = listmode_path)
    img = mlem_full()
    if outdir == '.':
        pass
    elif not os.path.isdir(outdir):
        os.mkdir(outdir, mode = 0o777)
    nef.save(img, outdir + '/recon_image.hdf5')
    nef.save(mlem_full, outdir + '/mlem_full.hdf5')

    doc_path = nef.doc_gen(mlem_full_without_data, img, outdir, outdir + '/recon_doc.md')
    print('generating doc at', doc_path)
    pypandoc.convert_file(outdir + '/recon_doc.md', 'pdf',
                          outputfile = outdir + '/recon_doc.md' + '.pdf')
    return img