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Thread: New approach enables the sorting of cells up to 38 times faster

  1. #1

    Default New approach enables the sorting of cells up to 38 times faster

    Medical News Today

    A team of engineers led by computer scientists at the University of California, San Diego, has developed a new approach that marries computer vision and hardware optimization to sort cells up to 38 times faster than is currently possible. The approach could be used for clinical diagnostics, stem cell characterization and other applications.

    The approach improves on a technique known as imaging flow cytometry, which uses a camera mounted on a microscope to capture the morphological features of hundreds to thousands of cells per second while the cells are suspended in a solution moving at approximately 4 meters per second. The technique sorts cells into different categories, for example benign or malignant cells, based on their shape and structure. If these features can be calculated fast enough, the cells can be sorted in real-time.

    "Previous techniques simply could not keep up with the image data streaming off of this high speed camera," said Ryan Kastner, a professor of computer science at the Jacobs School of Engineering at UC San Diego. "This has to potential to lead to a number of clinical breakthroughs, and we are working closely with UCLA and their industrial partners to commercialize our technology."

    Other researchers had previously discovered that the physical properties of cells could provide useful information about cell health, but previous techniques had been confined to academic research labs because measuring the cells of interest could take hours or even days. The new approach brings imaging flow cytometry closer to being used in a clinical setting.

    The microscope-mounted camera used in imaging flow cytometry operates at 140,000 frames per second. But algorithms currently in use take anywhere from 10 seconds to 0.4 seconds to analyze a single frame, depending on the programming language used - making the technique impractical.

    The researchers' new approach speeds processing speeds up to 11.94 milliseconds and 151.7 milliseconds depending on the type of hardware used. For the fastest results, engineers developed a custom hardware solution using a field-gate programmable array, or FPGA, which speeds up the process considerably. The slower results, which are still much faster than what's currently available, were obtained using a graphics processing unit, or GPU.

    The researchers' ultimate goal is to analyze the cell properties in real-time, and use that information to sort the cells. To do so, the sorting decision must be made in less than 10 milliseconds.

    The computer scientists presented their findings in September at the International Conference on Field Programmable Logic and Applications in Portugal.

    Computer vision algorithm and hardware optimization

    The ultimate goal of the algorithm is to determine the radius at every angle of the cell. This provides the necessary information to determine the cell's key features. Ideally this process needs to be performed on every frame in about 7 microseconds per frame. The algorithm must first detect the presence of the cell, then find the center of the cell, and finally determine the distance from this center to the cell wall for every angle, finding the cell's radius. To do this reliably, yet still meet stringent timing requirements, the algorithm was carefully modified to run faster on the FPGA.

    The Blob Search module analyzes the images to detect the cell's area. It then converts the black and white image of the cell into a digital image called a binary image, where each pixel carries either a zero or non-zero value. In this case, only the pixels representing the cell are highlighted. The system then constructs a graphical representation of the distribution of data in the image, known as a histogram. It then crops a 20 by 20 pixel image around the cell.

    The Interpolation step resizes the picture up to 200 by 200 pixels. It also generates a higher-contrast image of the cell. Then the Find Center module finds the center of the cell by converting the higher contrast images to binary images. It then counts the pixels with a non-zero value in each row and column of the image. The module averages the data from the two images produced by the Interpolation module to find the cell's center point. Finally, the algorithm determines the cell's shape and morphological properties by finding the darkest pixels on a line from the cell center at each angle of the image, which are considered to be part of the cell's wall.

    The researchers then carefully analyzed each step in the algorithm, and made modifications to the algorithm when necessary to implement it efficiently on the FPGA. When mapping to custom hardware, the designer must carefully consider the complexity of the algorithm versus the accuracy of the result. Certain algorithmic features, such as algorithms with larger number of decisions points or those requiring multiple passes over the data, make for a slow and inefficient hardware solution.

    They found that they obtained much better results with FPGA than with GPU. That's because FPGAs, unlike GPUs, can be configured so that they match the algorithm exactly. All operations occur at lightning-fast speeds. It takes the system under 500 microseconds to detect a cell and calculate its radius.
    First treatment in 2007. Pioneering ever since.


  2. #2
    Join Date
    Feb 2010
    peachtree city, ga

    Default Stem cell count

    I received an email today from a representative of celltex. She told me that they use a flow cytometry that views & counts the actual stem cell. She told me that this was very high tech. equipment that they have been using since opening the doors. So I wonder if this is the same technology. She also told me that the clinics in the U.S. do not use this equipment when counting stem cells. I will have to ask Dr. Malan this question for he told me that a computer counted my stem cells.

  3. #3


    Flow cytometry has been used for some time to do cell counts. However, there are actually some stem cells so small that it is difficult for some equipment to be able to count them as they are not designed for such low particle size. For the type of treatments CellTex is doing, the equipment they most likely have would be sufficient.

    I don't believe the representative is correct in stating that no clinics in the U.S. use this type of equipment. I know of one for sure that does.

    There are dozens of clinics in the U.S. To make such a broad statement seems more like a sales pitch to me.
    First treatment in 2007. Pioneering ever since.


  4. #4


    I am of course biased in favor of Celltex since that is where I bank my cells, and have had outstanding results using this to treat MS.

    But I am always interested in factual analysis of any stem cell operation.

    First let's make sure we are comparing apples to apples, because these are important due diligence questions patients seeking stem cell therapy need to ask. There two major categories I am aware of:

    1) Same day stem cell preparations done in a physicians office, separated from fat or born marrow, and administered back to the patient that same day. That extracted from adipose tissue is referred to as Stromal Vascular Fraction (SVF) and contains a mixture of cells, many that have healing properties, in addition to the most therapeutic, mesenchymal stem cells MSCs). A lipo-suction of 8-12 oz of fat may yield around 50 million MSCs. Some clinics say they can deliver billions of cells from SVF, but are they counting all the cells, or just the MSCs?

    2) Expanded cell preparations done over several weeks in a cell lab, and then cryo preserved for later use.

    Celltex falls into the second category (and there are very few operations to compare this to in the U.S., other than University hospital labs). For this they utilize a multi-step process, of which flow cytometry is just one. When the cells are grow in a lab to reach a higher dose level, the onus is much higher to make sure the cells are identical to the original starting cells. The reason to go to all this trouble is to achieve higher doses, which may be required for more serious disease. In my case, I received 3 IV's a week apart, each containing 200 million pure mesenchymal stem cells.
    Their process is detailed here

    To make it easier to compare, please post any links to other labs or doctors methods, which details the process. Feel free to post corrections or further
    examples, I'm just a self taught medical student.

  5. #5


    But how does anyone know they really do this? How does anyone get proof beyond a shadow of a doubt that what a clinic/doctor/stem cell bank says is really true or not? And how would any of these clinics know what others are doing? It gets really confusing out there.

    Since you have had 3 treatments (or is this considered one treatment done over 3 weeks) how are you doing? Do you think you will need more? I am afraid the expense would be too much for a lot of people, but I am happy for those who can get treated and give information out that may be helpful to others in the future.

  6. #6


    Donna - I know that SammyJo has had a positive experience with her treatment(s). I will let her comment on them.

    SammyJo - What peg stated is that the representative told her that Celltex was the only company that uses flow cytometry in the U.S. to do cell counts. My response was that this sounded more like a sales pitch than fact. Perhaps, the representative meant the processing technique coupled with the use of the flow cytometer to identify certain cells was not utilized by others, but just stating that they are the only company to use a flow cytometer to count cells is not true.

    Is this a case of misunderstanding? I am inclined to think so, but I wasn't in on the conversation so I can't say for sure. I think that the processing is being confused with just the fact that a flow cytometer is used. Anyway, that's how I see it.
    First treatment in 2007. Pioneering ever since.


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