well in some way you will have to use isnan. You could use bwconncomp to find "lonely" Nans. Like in this example:
%%create some sample data
data = rand(10); % make a random sample
data(data>0.9) = NaN; % create some nans
data(1:6,1:6) = NaN; % make an island
c = bwconncomp(isnan(data))
s = cellfun(@numel,c.PixelIdxList)
single_nan_ind = s==1
single_nans = cellfun(@(x) ind2sub(x,size(data)),c.PixelIdxList(single_nan_ind),'UniformOutput',false)
The ones you are looking for would be in single_nans.
