Performance issue with reading DICOM data into cell array - matlab

Question

I need to read 4000 or more DICOM files. I have written the following code to read the files and store the data into a cell array so I can process them later. A single DICOM file contains 128 * 931 data. But once I execute the code it took more than 55 minutes to complete the iteration. Can someone point out to me the performance issue of the following code?
% read the file information form the disk to memory
readFile=dir('d:\images','*.dcm');
for i=1:4000
% Read the information form the dicom files in to arrays
data{i}=dicomread(readFile(i).name);
info{i}=dicominfo(readFile(i).name);
data_double{i}=double(data{1,i}); % convert 16 bit data into double
first_chip{i}=data_double{1,i}(1:129,1:129); % extracting first chip data into an array
end

Answer 1

You are reading 128*931*4000 pixels into memory (assuming 16-bit values, that's nearly 1 GB), converting that to doubles (4 GB) and extracting a region (129*129*4000*8 = 0.5 GB). You are keeping all three of these copies, which is a terrible amount of data! Try not keeping all that data around:
readFile = dir('d:\images','*.dcm');
first_chip = cell(size(readFile));
info = cell(size(readFile));
for ii = 1:numel(readFile)
info{ii} = dicominfo(readFile(ii).name);
data = dicomread(info{ii});
data = (1:129,1:129); % extracting first chip data
first_chip{ii} = double(data); % convert 16 bit data into double
end
Here, I have pre-allocated the first_chip and info arrays. If you don't do this, the arrays will be re-allocated every time you add an element, causing expensive copies. I have also extracted the ROI first, then converted to double, as suggested by Rahul in his answer. Finally, I am re-using the DICOM info structure to read the file. I don't know if this makes a big difference in speed, but it saves the dicomread function some effort.
But note that this process will still take a considerable amount of time. Reading DICOM files is complex, and takes time. I suggest you read them all in once, then save the first_chip and info cell arrays into a MAT-file, which will be a lot faster to read in at a later time.

Answer 2

You can run the profiler to check which part of the code is taking up most of the time! But as far as it looks to me is that its your iteration size & the time taken is very much genuine. You could try and use parallel computing ( parfor loop) if you have a multicore processor, that should decrease the runtime significantly depending upon the number of cores that you have.
One suggestion would be to exctract the 'first chip data' first and then convert it to double, as the conversion process takes a significant amount of time.