Beispiel #1
0
def main(file_name, smooth=3):
    div = [25]
    #div = [13,15,19,23,25]
    #div = [5,7,9,11,13,15,19,23,25]
    #div = int(div)
    path, fname, ext_fname = sct.extract_fname(file_name)
    exit = 0

    print 'file to be processed: ', file_name

    print 'Applying propseg to get the centerline as a binary image...'
    #fname_seg = fname+'_seg'
    fname_centerline = fname + '_centerline'
    cmd = 'sct_propseg -i ' + file_name + ' -o . -t t2 -centerline-binary'
    sct.run(cmd)

    print 'centerline smoothing...'
    fname_smooth = fname_centerline + '_smooth'
    print 'Gauss sigma: ', smooth
    cmd = 'fslmaths ' + fname_centerline + ' -s ' + str(
        smooth) + ' ' + fname_smooth + ext_fname
    sct.run(cmd)

    for d in div:
        add = d - 1
        e = 1
        print 'generating the centerline...'
        while e == 1:
            add += 1
            #e = centerline.returnCenterline(fname_smooth+ext_fname, 1, add)
            e = centerline.check_nurbs(add, None, None,
                                       fname_smooth + ext_fname)
            if add > 30:
                exit = 1
                break

        if exit == 1:
            break
        d = add
        size = e
        nurbs_ctl_points = int(size) / d

        #d = returnCenterline(fname_smooth+ext_fname, d)

        print 'straightening...  d = ', str(d)
        #fcenterline = './centerlines/'+fname_smooth+'_'+str(d)+'_centerline.nii.gz'
        cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_smooth + ext_fname + ' -n ' + str(
            nurbs_ctl_points)
        sct.run(cmd)
        '''
        print 'applying propseg'
        fname_straight = fname+'_straight'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        cmd = 'sct_propseg -i '+fname_straight+' -t t2'

        '''

        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname + '_straight_seg' + ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 ' + fname_smooth + ext_fname + ' ' + final_file_name + ' warp_curve2straight.nii.gz'

        sct.run(cmd)

        print 'annalyzing the straightened file'
        linear_fitting.returnSquaredErrors(final_file_name, d, size)

    os.remove(fname_centerline + ext_fname)
    os.remove(fname_smooth + ext_fname)
    os.remove('warp_curve2straight.nii.gz')
    os.remove('warp_straight2curve.nii.gz')
def main(file_name, smooth = 3):
    div = [25]
    #div = [13,15,19,23,25]
    #div = [5,7,9,11,13,15,19,23,25]
    #div = int(div)
    path, fname, ext_fname = sct.extract_fname(file_name)
    exit = 0

    print 'file to be processed: ',file_name

    print 'Applying propseg to get the centerline as a binary image...'
    #fname_seg = fname+'_seg'
    fname_centerline = fname+'_centerline'
    cmd = 'sct_propseg -i '+file_name+' -o . -t t2 -centerline-binary'
    sct.run(cmd)


    print 'centerline smoothing...'
    fname_smooth = fname_centerline+'_smooth'
    print 'Gauss sigma: ', smooth
    cmd = 'fslmaths '+fname_centerline+' -s '+str(smooth)+' '+fname_smooth+ext_fname
    sct.run(cmd)


    for d in div:
        add = d - 1
        e = 1
        print 'generating the centerline...'
        while e == 1:
            add += 1
            #e = centerline.returnCenterline(fname_smooth+ext_fname, 1, add)
            e = centerline.check_nurbs(add, None, None, fname_smooth+ext_fname)
            if add > 30:
                exit = 1
                break

        if exit == 1:
            break
        d = add
        size = e
        nurbs_ctl_points = int(size)/d

        #d = returnCenterline(fname_smooth+ext_fname, d)



        print 'straightening...  d = ', str(d)
        #fcenterline = './centerlines/'+fname_smooth+'_'+str(d)+'_centerline.nii.gz'
        cmd = 'sct_straighten_spinalcord -i '+file_name+' -c '+fname_smooth+ext_fname+' -n '+str(nurbs_ctl_points)
        sct.run(cmd)

        '''
        print 'applying propseg'
        fname_straight = fname+'_straight'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        cmd = 'sct_propseg -i '+fname_straight+' -t t2'

        '''

        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 '+fname_smooth+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'

        sct.run(cmd)
        

        print 'annalyzing the straightened file'
        linear_fitting.returnSquaredErrors(final_file_name, d, size)

    os.remove(fname_centerline+ext_fname)
    os.remove(fname_smooth+ext_fname)
    os.remove('warp_curve2straight.nii.gz')
    os.remove('warp_straight2curve.nii.gz')
def main():
    div = [3,5,7,9,11,13,15,19,23,25]
    nurbs_ctl_points = param.nurbs_ctl_points
    fitting_method = param.fitting_method
    sigma = param.sigma
    centerline = param.centerline
    s = 0
    d = 0
    exit = 0
    file_name = ''
    warp = param.warp

    try:
        opts, args = getopt.getopt(sys.argv[1:],'hi:M:n:d:s:c:v:w:r:h:')
    except getopt.GetoptError as err:
        print str(err)
        usage()
    for opt, arg in opts:
        if opt == '-h':
            usage()
        elif opt in ('-i'):
            file_name = arg
        elif opt in ('-M'):
            fitting_method = arg
        elif opt in ('-n'):
            nurbs_ctl_points = int(arg)
        elif opt in ('-d'):
            d = 1
            div = int(arg)
        elif opt in ('-s'):
            s = 1
            sigma = str(arg)
        elif opt in ('-c'):
            centerline = str(arg)
            fname_centerline = centerline
        elif opt in ('-v'):
            verbose = int(arg)
        elif opt in ('-w'):
            write = arg
        elif opt in ('-r'):
            remove = arg

    print 'file to be processed: ',file_name
    path, fname, ext_fname = sct.extract_fname(file_name)

    if not fitting_method == 'NURBS' and not fitting_method == 'polynomial' and not fitting_method == 'non_parametrique' and not fitting_method == 'smooth':
        usage()

    if centerline == None:
        # Generating centerline using propseg (Warning: be sure propseg work well with the input file)
        print 'Applying propseg to get the centerline as a binary image...'
        fname_centerline = fname+'_centerline'
        cmd = 'sct_propseg -i ' + file_name + ' -o . -t t2 -centerline-binary'
        sct.run(cmd)
    else:
        path, fname_centerline, ext_fname = sct.extract_fname(centerline)

    if s is not 0:
        print 'centerline smoothing...'
        fname_smooth = fname_centerline+'_smooth'
        print 'Gauss sigma: ', s
        cmd = 'fslmaths ' + fname_centerline + ' -s ' + str(s) + ' ' + fname_smooth + ext_fname
        sct.run(cmd)
        fname_centerline = fname_smooth+ext_fname
    else:
        fname_centerline = centerline

    if fitting_method == 'NURBS':
        if not d and not nurbs_ctl_points:
            for d in div:
                add = d - 1
                e = 1
                print 'generating the centerline...'

                # This loops stands for checking if nurbs will work with d
                while e == 1:
                    add += 1
                    e = centerline.check_nurbs(add, None, None, fname_smooth+ext_fname)
                    if add > 30:
                        exit = 1
                        break
                if exit == 1:
                    break
                d = add
                size = e

                nurbs_ctl_points = int(size)/d
        elif not nurbs_ctl_points:
            nurbs_ctl_points = int(size)/d

            print 'straightening...  d = ', str(d)

            # STRAIGHTEN USING NURBS
            cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_centerline + ' -n ' + str(nurbs_ctl_points)
            sct.run(cmd)

            print 'apply warp to segmentation'
            #final_file_name = fname+'_straightttt_seg'+ext_fname
            final_file_name = fname + '_straight_seg' + ext_fname
            #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
            cmd = 'sct_WarpImageMultiTransform 3 ' + fname_centerline + ' ' + final_file_name + ' warp_curve2straight.nii.gz'

            sct.run(cmd)

            print 'annalyzing the straightened file'
            linear_fitting.returnSquaredErrors(final_file_name, d, size)

    elif fitting_method == 'polynomial':
        # STRAIGHTEN USING POLYNOMIAL FITTING
        cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_smooth + ext_fname + ' -f polynomial -v 2'
        d = 'polynomial'
        size = 13
        # STRAIGHTEN USING 'non_parametric'
        sct.run(cmd)

        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 '+fname_smooth+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'

        sct.run(cmd)

    elif fitting_method == 'smooth':
        # STRAIGHTEN USING POLYNOMIAL FITTING
        cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_centerline  + ' -f smooth -v 2'
        d = 'smooth'
        size = 13
        # STRAIGHTEN USING 'non_parametric'
        sct.run(cmd)

        if warp == 1:
            print 'apply warp to segmentation'
            #final_file_name = fname+'_straightttt_seg'+ext_fname
            final_file_name = fname+'_straight_seg'+ext_fname
            #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
            cmd = 'sct_WarpImageMultiTransform 3 '+fname_centerline+' '+final_file_name+' warp_curve2straight.nii.gz'
        else:
            print 'Applying propseg to the straightened volume...'
            fname_straightened = fname+'_straight'
            cmd = 'sct_propseg -i ' + fname_straightened + ext_fname +' -o . -t t2 -centerline-binary'
            final_file_name = fname_straightened + '_centerline' + ext_fname

        sct.run(cmd)

    elif fitting_method == 'non-parametric':
        cmd = 'sct_straighten_spinalcord -i '+file_name+' -c '+fname_smooth+ext_fname+' -f non_parametrique -v 2'
        d = 'polynomial'
        size = 13
        # STRAIGHTEN USING 'non_parametric'
        sct.run(cmd)

        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 '+fname_smooth+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'

        sct.run(cmd)
        

    print 'annalyzing the straightened file'
    linear_fitting.returnSquaredErrors(final_file_name, d, size)

    os.remove(fname_centerline+ext_fname)
    os.remove(fname_smooth+ext_fname)
    os.remove('warp_curve2straight.nii.gz')
    os.remove('warp_straight2curve.nii.gz')
Beispiel #4
0
def main():
    div = [3, 5, 7, 9, 11, 13, 15, 19, 23, 25]
    nurbs_ctl_points = param.nurbs_ctl_points
    fitting_method = param.fitting_method
    sigma = param.sigma
    centerline = param.centerline
    s = 0
    d = 0
    exit = 0
    file_name = ''
    warp = param.warp

    try:
        opts, args = getopt.getopt(sys.argv[1:], 'hi:M:n:d:s:c:v:w:r:h:')
    except getopt.GetoptError as err:
        print str(err)
        usage()
    for opt, arg in opts:
        if opt == '-h':
            usage()
        elif opt in ('-i'):
            file_name = arg
        elif opt in ('-M'):
            fitting_method = arg
        elif opt in ('-n'):
            nurbs_ctl_points = int(arg)
        elif opt in ('-d'):
            d = 1
            div = int(arg)
        elif opt in ('-s'):
            s = 1
            sigma = str(arg)
        elif opt in ('-c'):
            centerline = str(arg)
            fname_centerline = centerline
        elif opt in ('-v'):
            verbose = int(arg)
        elif opt in ('-w'):
            write = arg
        elif opt in ('-r'):
            remove = arg

    print 'file to be processed: ', file_name
    path, fname, ext_fname = sct.extract_fname(file_name)

    if not fitting_method == 'NURBS' and not fitting_method == 'polynomial' and not fitting_method == 'non_parametrique' and not fitting_method == 'smooth':
        usage()

    if centerline == None:
        # Generating centerline using propseg (Warning: be sure propseg work well with the input file)
        print 'Applying propseg to get the centerline as a binary image...'
        fname_centerline = fname + '_centerline'
        cmd = 'sct_propseg -i ' + file_name + ' -o . -t t2 -centerline-binary'
        sct.run(cmd)
    else:
        path, fname_centerline, ext_fname = sct.extract_fname(centerline)

    if s is not 0:
        print 'centerline smoothing...'
        fname_smooth = fname_centerline + '_smooth'
        print 'Gauss sigma: ', s
        cmd = 'fslmaths ' + fname_centerline + ' -s ' + str(
            s) + ' ' + fname_smooth + ext_fname
        sct.run(cmd)
        fname_centerline = fname_smooth + ext_fname
    else:
        fname_centerline = centerline

    if fitting_method == 'NURBS':
        if not d and not nurbs_ctl_points:
            for d in div:
                add = d - 1
                e = 1
                print 'generating the centerline...'

                # This loops stands for checking if nurbs will work with d
                while e == 1:
                    add += 1
                    e = centerline.check_nurbs(add, None, None,
                                               fname_smooth + ext_fname)
                    if add > 30:
                        exit = 1
                        break
                if exit == 1:
                    break
                d = add
                size = e

                nurbs_ctl_points = int(size) / d
        elif not nurbs_ctl_points:
            nurbs_ctl_points = int(size) / d

            print 'straightening...  d = ', str(d)

            # STRAIGHTEN USING NURBS
            cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_centerline + ' -n ' + str(
                nurbs_ctl_points)
            sct.run(cmd)

            print 'apply warp to segmentation'
            #final_file_name = fname+'_straightttt_seg'+ext_fname
            final_file_name = fname + '_straight_seg' + ext_fname
            #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
            cmd = 'sct_WarpImageMultiTransform 3 ' + fname_centerline + ' ' + final_file_name + ' warp_curve2straight.nii.gz'

            sct.run(cmd)

            print 'annalyzing the straightened file'
            linear_fitting.returnSquaredErrors(final_file_name, d, size)

    elif fitting_method == 'polynomial':
        # STRAIGHTEN USING POLYNOMIAL FITTING
        cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_smooth + ext_fname + ' -f polynomial -v 2'
        d = 'polynomial'
        size = 13
        # STRAIGHTEN USING 'non_parametric'
        sct.run(cmd)

        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname + '_straight_seg' + ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 ' + fname_smooth + ext_fname + ' ' + final_file_name + ' warp_curve2straight.nii.gz'

        sct.run(cmd)

    elif fitting_method == 'smooth':
        # STRAIGHTEN USING POLYNOMIAL FITTING
        cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_centerline + ' -f smooth -v 2'
        d = 'smooth'
        size = 13
        # STRAIGHTEN USING 'non_parametric'
        sct.run(cmd)

        if warp == 1:
            print 'apply warp to segmentation'
            #final_file_name = fname+'_straightttt_seg'+ext_fname
            final_file_name = fname + '_straight_seg' + ext_fname
            #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
            cmd = 'sct_WarpImageMultiTransform 3 ' + fname_centerline + ' ' + final_file_name + ' warp_curve2straight.nii.gz'
        else:
            print 'Applying propseg to the straightened volume...'
            fname_straightened = fname + '_straight'
            cmd = 'sct_propseg -i ' + fname_straightened + ext_fname + ' -o . -t t2 -centerline-binary'
            final_file_name = fname_straightened + '_centerline' + ext_fname

        sct.run(cmd)

    elif fitting_method == 'non-parametric':
        cmd = 'sct_straighten_spinalcord -i ' + file_name + ' -c ' + fname_smooth + ext_fname + ' -f non_parametrique -v 2'
        d = 'polynomial'
        size = 13
        # STRAIGHTEN USING 'non_parametric'
        sct.run(cmd)

        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname + '_straight_seg' + ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 ' + fname_smooth + ext_fname + ' ' + final_file_name + ' warp_curve2straight.nii.gz'

        sct.run(cmd)

    print 'annalyzing the straightened file'
    linear_fitting.returnSquaredErrors(final_file_name, d, size)

    os.remove(fname_centerline + ext_fname)
    os.remove(fname_smooth + ext_fname)
    os.remove('warp_curve2straight.nii.gz')
    os.remove('warp_straight2curve.nii.gz')
Beispiel #5
0
def main(file_name, smooth = 3):
    div = [5]
    #,7,9,11,13,15,19,23,25]
    #div = int(div)
    path, fname, ext_fname = sct.extract_fname(file_name)


    print 'file to be processed: ',file_name

    print 'Applying propseg...'
    fname_seg = fname+'_seg'
    cmd = 'sct_propseg -i '+file_name+' -o . -t t2'
    sct.run(cmd)


    print 'image smoothing...'
    fname_smooth = fname_seg+'_smooth'
    print 'Gauss sigma: ', smooth
    cmd = 'fslmaths '+fname_seg+' -s '+str(smooth)+' '+fname_smooth+ext_fname
    sct.run(cmd)


    for d in div:
        add = d - 1
        e = 1
        print 'generating the centerline...'
        while e == 1:
            add += 1
            e = centerline.returnCenterline(fname_smooth+ext_fname, 1, add)
            
        d = add

        #d = returnCenterline(fname_smooth+ext_fname, d)



        print 'straightening...  d = ', str(d)
        fcenterline = './centerlines/'+fname_smooth+'_'+str(d)+'_centerline.nii.gz'
        cmd = 'sct_straighten_spinalcord -i '+file_name+' -c '+fcenterline
        sct.run(cmd)




        '''
        print 'applying propseg'
        fname_straight = fname+'_straight'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        cmd = 'sct_propseg -i '+fname_straight+' -t t2'

        '''
        print 'apply warp to segmentation'
        #final_file_name = fname+'_straightttt_seg'+ext_fname
        final_file_name = fname+'_straight_seg'+ext_fname
        #cmd = 'sct_WarpImageMultiTransform 3 '+fname_seg+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'
        cmd = 'sct_WarpImageMultiTransform 3 '+fname_smooth+ext_fname+' '+final_file_name+' warp_curve2straight.nii.gz'

        sct.run(cmd)
        

        print 'annalyzing the straightened file'
        linear_fitting.returnSquaredErrors(final_file_name, d)

    os.remove(fname_seg+ext_fname)
    os.remove(fname_smooth+ext_fname)
    os.remove('warp_curve2straight.nii.gz')
    os.remove('warp_straight2curve.nii.gz')