Error using fieldnames. Invalid argument of type 'cell'. Input must be a structure or a Java or COM object.

Hi,

I am trying to open a BIDS format folder in lead dbs developer mode.

I am getting this error :

"

Error using fieldnames

Invalid input argument of type 'cell'. Input must be a structure or a Java or COM object.

Error in BIDSFetcher/getPreopAnat (line 300)

templateOrder = fieldnames(obj.spacedef.norm_mapping)';

"

These are the parts of the code in the same file "BIDSFetcher.m" where it refers to obj.spacedef.name:

% Set base dir and base name
templateSpace = obj.spacedef.name;
baseName = fullfile(LeadDBSDirs.normDir, 'transformations', ['sub-', subjId, '_from-']);
"
and

% Set normalized anat images
templateSpace = obj.spacedef.name;
session = fieldnames(coregAnat);
for i=1:length(session)
    modality = fieldnames(coregAnat.(session{i}));
    for j=1:length(modality)
        anat = strrep(coregAnat.(session{i}).(modality{j}), LeadDBSDirs.coregDir, LeadDBSDirs.normDir);
        normAnat.(session{i}).(modality{j}) = strrep(anat, obj.anchorSpace, templateSpace);

Is it possible to make obj.spacedef.name a structure somehow?

I DO have R2021b installed, however my PhD supervisor also has R2021b installed and does not have the same error. He does have a lot more matlab applications installed than me, and it would be very difficult to find out which app is responsbile for the differene between our machines, considering he has so many that I do not.

Do you have any ideas on a fix for this?

Thanks

[Mario Malic]

In which line of your code do you get an error?

[Fiona]

In this line (300)

templateOrder = fieldnames(obj.spacedef.norm_mapping)';

from:

"

Error using fieldnames

Invalid input argument of type 'cell'. Input must be a structure or a Java or COM object.

Error in BIDSFetcher/getPreopAnat (line 300)

templateOrder = fieldnames(obj.spacedef.norm_mapping)';

"

% Set pre-defined orders
preniiOrder = obj.settings.prenii_order;
templateOrder = fieldnames(obj.spacedef.norm_mapping)';
preopImageOrder = [preniiOrder, setdiff(templateOrder, preniiOrder, 'stable')];

Answer 1

[Walter Roberson]

If you look near line 240 of https://github.com/netstim/leaddbs/blob/master/ea_normalize_ants.m you will see that the code assumes that spacedef.norm_mapping is a cell. Code should not be trying to take fieldnames of it.

[Fiona]

However the same code works for my supervisor, who is running the same version of leaddbs on the same version of matlab.... What could explain this? Our only difference is the number of apps installed in MATLAB 2021b.

[Fiona]

The ea_normalize_ants.m file in my current matlab leaddbs path is different to the one you referenced, possibly because I am using the developer and not the master branch. In my developer branch there are only 129 lines of code (see below) in the ea_normalize_ants.m file.

I was previously using the master branch of leaddbs (and it was working) which uses the same ea_noramlize_ants.m code as the one you referenced, including the lines around 240 referencing spacedef.norm_mapping. However I cannot use the master version for the tools I need.

See below:

function varargout = ea_normalize_ants(options)
% This is a function that normalizes both a copy of transversal and coronal
% images into MNI-space. The goal was to make the procedure both robust and
% automatic, but still, it must be said that normalization results should
% be taken with much care because all reconstruction results heavily depend
% on these results. Normalization of DBS-MR-images is especially
% problematic since usually, the field of view doesn't cover the whole
% brain (to reduce SAR-levels during acquisition) and since electrode
% artifacts can impair the normalization process. Therefore, normalization
% might be best archieved with other tools that have specialized on
% normalization of such image data.
%
% The procedure used here uses the ANTs Syn approach to map a patient's
% brain to MNI space directly.
% __________________________________________________________________________________
% Copyright (C) 2015 Charite University Medicine Berlin, Movement Disorders Unit
% Andreas Horn


if ischar(options) % return name of method.
    varargout{1} = 'ANTs (Avants 2008)';
    varargout{2} = 1; % dummy output
    varargout{3} = 1; % hassettings.
    varargout{4} = 1; % is multispectral
    return
end

usefa = options.prefs.machine.normsettings.ants_usefa;
usebrainmask=0;

cnt=1;

% TODO: Take care of FA
spacedef = options.bids.spacedef;
if usefa && spacedef.hasfa % first put in FA since least important (if both an FA template and an fa2anat file is available)
    if exist([options.prefs.fa2anat],'file') % recheck if now is present.
        disp('Including FA information for white-matter normalization.');
        template{cnt} = [ea_space(options),'fa.nii'];
        moving{cnt} = [bprfx,options.prefs.fa2anat];
        weights(cnt) = 0.5;
        cnt = cnt+1;
    elseif exist([options.prefs.fa],'file') % recheck if now is present.
        disp('Including FA information for white-matter normalization (weight = 0.5).');
        ea_coregimages(options,[bprfx,options.prefs.fa],[anatpresent{1}],[bprfx,options.prefs.fa2anat],{},0,[],1);
        template{cnt} = [ea_space(options),'fa.nii'];
        moving{cnt} = [bprfx,options.prefs.fa2anat];
        weights(cnt) = 0.5;
        cnt = cnt+1;
    end
end

disp(['Pre-op ', strjoin(fieldnames(options.subj.coreg.anat.preop), ', '), ' images included for normalization']);
imagePresent = flip(struct2cell(options.subj.coreg.anat.preop)); % Flip the order so anchor will be the last one

% The convergence criterion for the multivariate scenario is a slave to the
% last metric you pass on the ANTs command line.
for i = 1:length(imagePresent)
    % Set template image
    template{cnt} = ea_matchTemplate(imagePresent{i}, spacedef);
    
    % Segment and mask image when needed.
    if usebrainmask
        moving{cnt} = ea_maskimg(imagePresent{i});
    else
        moving{cnt} = imagePresent{i};
    end
    
    % Set weights
    weights(cnt) = 1.25;
    cnt = cnt+1;
end

% Add segmentations in case present (under coregistration/segmentations)
segmentations = ea_regexpdir([options.subj.subjDir, filesep, 'segmentations'], '.*\.nii(\.gz)?$', 0);
if ~isempty(segmentations)
    for i=1:length(segmentations)
        [~, segName] = ea_niifileparts(segmentations{i});
        segTemplate = ea_regexpdir([ea_space, 'segmentations'], [segName, '\.nii(\.gz)?$'], 0);
        if ~isempty(segTemplate) % Found matching template in template space segmentations folder
            disp(['Including ', segName, ' segmentation for segment based assistance (weight = 20).']);
            moving = [segmentations{i}, moving]; % append to front (since last one is convergence critical)
            template = [segTemplate{1}, template];
            weights = [20, weights]; % set weight to 20 - DO NOT CHANGE THIS VALUE BELOW 3. IF VALUE IS CHANGED, SEGMENTATIONS WILL BE CONSIDERED SLABS IN ea_ants_nonlinear ~line 63 - would need to be changed there, as well.
        end
    end
end

output_image = options.subj.norm.anat.preop.(options.subj.AnchorModality);
output_transform_prefix = fullfile(fileparts(options.subj.norm.transform.forwardBaseName), 'antsout');

ea_mkdir(fileparts(output_image));
ea_mkdir(fileparts(output_transform_prefix));

ea_ants_nonlinear(template, moving, output_image, weights, output_transform_prefix, options);

% Move transformation file
movefile([output_transform_prefix 'Composite.nii.gz'], [options.subj.norm.transform.forwardBaseName, 'ants.nii.gz']);
movefile([output_transform_prefix 'InverseComposite.nii.gz'], [options.subj.norm.transform.inverseBaseName, 'ants.nii.gz']);

ea_apply_normalization(options);

% Add methods dump
modality = regexp(imagePresent, '(?<=_)[^\W_]+(?=\.nii(\.gz)?$)', 'match', 'once');
if options.prefs.machine.normsettings.ants_scrf
    [scit, lcit] = ea_getspacedefcit;
    cits={
        'Avants, B. B., Epstein, C. L., Grossman, M., & Gee, J. C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1), 26?41. http://doi.org/10.1016/j.media.2007.06.004'
        'Schoenecker, T., Kupsch, A., Kuehn, A. A., Schneider, G.-H., & Hoffmann, K. T. (2009). Automated Optimization of Subcortical Cerebral MR Imaging-Atlas Coregistration for Improved Postoperative Electrode Localization in Deep Brain Stimulation. AJNR Am J Neuroradiol, 30(10), 1914?1921. http://doi.org/10.3174/ajnr.A1741'};
    if ~isempty(lcit)
        cits = [cits;{lcit}];
    end
    
    ea_methods(options,['Pre- (and post-) operative acquisitions were spatially normalized into ',ea_getspace,' space ',scit,' based on preoperative acquisition(s) (',strjoin(modality, ', '),') using the'...
        ' SyN registration approach as implemented in Advanced Normalization Tools (Avants 2008; http://stnava.github.io/ANTs/).',...
        ' Nonlinear deformation into template space was achieved in five stages: After two linear (rigid followed by affine) steps, ',...
        ' A nonlinear (whole brain) SyN-registration stage was followed by two nonlinear SyN-registrations that consecutively focused on the area of interest ',...
        ' as defined by subcortical masks in Schoenecker 2008.'],cits);
else
    [scit, lcit] = ea_getspacedefcit;
    cits = {'Avants, B. B., Epstein, C. L., Grossman, M., & Gee, J. C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1), 26?41. http://doi.org/10.1016/j.media.2007.06.004'};
    if ~isempty(lcit)
        cits = [cits;{lcit}];
    end
    
    ea_methods(options,['Pre- (and post-) operative acquisitions were spatially normalized into ',ea_getspace,' space ',scit,' based on preoperative acquisition(s) (',strjoin(modality, ', '),') using the'...
        ' SyN registration approach as implemented in Advanced Normalization Tools (Avants 2008; http://stnava.github.io/ANTs/).',...
        ' Nonlinear deformation into template space was achieved in three stages: After two linear (rigid followed by affine) steps, ',...
        ' a nonlinear (whole brain) SyN registration stage was added.'],cits);
end