Month: September 2012

I am going to utilize available PCs in labs of our department to process images. Generating intensity attenuated images takes much time (more than five minutes for one single forty layered image). It would be better to run the processing modules on many machines at the same time. Images on a NAS can be accessible (see more details in my previous posting).

In my first few trials, the new system seemed work. But after that, the network resource where all the executables are located are not accessible any more with a strange error message.

Not enough storage is available to process this command.

I came across a few interesting articles.

• http://support.microsoft.com/kb/106167
• http://support.microsoft.com/?scid=kb%3Ben-us%3B285089&x=15&y=11

At first, it scared me a little bit because the articles say that registries should be backed up and restored. I just tried without backing up the registries to test my luck. 😉

After adding the item in my registry, I restarted my computer and run my image processing sub modules. It seems work for now. I will post if I come across any other problem regarding this issue.

It takes much time to compose large images into a single image. In my experiments, I am using forty images to generate an intensity attenuated image. This is even more true when the size of an image is huge like about 12,000 x 9,600. One image has 115,200,000 pixels in this size. Think about forty images when they are processed. It took me eight seconds to compose two images into one with a simulated transparent channel. More than five minutes are needed to generate a single composed image from forty images. I have around 9,628 images. From my rough calculation it will take my machine more than a month to process all the images. This is not a big problem since this process should be done only one time. But I do not like this since I have more tissue samples to process.

My idea is to use multiple computers at the same time in our department’s network. NAS (Network Attached Storage) can be a solution to address this issue. Using the network storage is a good approach because the bottle neck of this system is not reading and writing image data files but processing images. (I realized that reading/writing image files from an NAS take much more time than processing them from my experiments. It will not reduce total consuming time as I initially expect but is worth to use the minimal parallelism.) So it is good to use as many computers as possible to reduce whole processing time.

I purchased a NAS that is Synology DiskStation; DS212j along with two hard disk drives; 2TB and 3TB. This will give me enough space at least for a while.

I have one desktop PC and one Mac Pro under a router in my office. The new NAS is attached to the router. Four high performance PCs in a lab of the ECE department are available for five days in a week. Eight Mac minis in my Mobile App Lab are also usable. I am going to utilize all those computers as much as possible.

Here is a rough system design for it. Tools in KESMSuite should be expanded to be run on this configuration. The port number 80 (this is a default port for HTTP) for the IP address of the NAS should be ‘Port Forwarding’ in the router settings. To my surprise, this port forwarding is enough for this system to work.

KESM (Knife-Edge Scanning Microscope) can scan really thin (sub-micron level) images from animal tissues. Thin slices are very critical to create accurate volumetric 3D images since the depth structure can be restored more accurately. However, one single image does not make much sense to us when it is shown one by one.

It has bunch of dots and short lines instead of meaningful structure. It would be better to be seen if several images are overlapped with depth attenuation in their intensity levels.

So I implemented a method to create intensity attenuated images. Creating this kind of images is not new because we can use an image editing tool such as Photoshop to create multiple layers in which layer has an alpha channel to set its transparent level. My method does not use the alpha channel and does not need to use a specific image file format that supports the alpha channel. Original JPEG image files can be used without converting them into transparent-support-file-formats. Note that JPEG does not support alpha channel so that you cannot make it transparent with a standard tool.

Here is a sample image. One more good thing is that this image composition can be done automatically using my KESMSuite that is actively being developed. The sample image was generated using 40 consecutive images. To make a realistic pseudo 3D images, the intensity attenuation factor is calculated from a quadratic function of the depth.