Browsing by Author "Dr. David Lalush, Committee Member"

Filter results by typing the first few letters
Now showing 1 - 3 of 3
  • No Thumbnail Available
    A Passive Pumping Microfluidic Coulter Counter
    (2009-11-20) McPherson, Amy; Dr. David Lalush, Committee Member; Dr. Glenn Walker, Committee Chair; Dr. Greg McCarty, Committee Member
    As a result of the growing costs of healthcare technology, there is an increasing need for medical diagnostic tools that provide accurate information in a portable, low-cost platform. A microfluidic device using on-chip passive pumping was characterized for use as a particle counter. A detection circuit interfaced with electrodes in the microfluidic chip to provide an excitation signal and to detect electrical activity. Flow occurred due to a Young-Laplace pressure gradient between a 1.2 mm diameter inlet and a 4 mm diameter reservoir when 0.5 μL fluid droplets were applied to the inlet using a micropipette. Polystyrene particles were enumerated using the resistive pulse technique, in which particles can be detected based on the difference in particle conductivity from that of the surrounding medium. Particles counted using the passive flow method demonstrated mean particle counts that were within 13% of those detected using a syringe pump, while all pumping methods displayed particle counts that were within 16% of the count obtained using a hemacytometer. Three different sample loading patterns were compared; the methods varied only in the order of sample and wash fluid administration. Zero, one, or two wash droplets were loaded after the first of two sample droplets. No statistical difference was detected in the mean particle counts for all loading patterns using the passive method (p > 0.05). This passive pumping method is easily implemented using only a micropipette, thus reducing the cost and complexity of particle enumeration, and the method can be implemented in a point-of-care (POC) device for a highly portable, cost-effective particle counter. These methods obtained particle counts that were also consistent with syringe pumping (p > 0.05).
  • No Thumbnail Available
    Performance of Microcalcification Detection Algorithms
    (2005-07-21) Srivastava, Vaibhav; Dr. Wesley Snyder, Committee Chair; Dr. Edward Grant, Committee Member; Dr. David Lalush, Committee Member; Dr. Huaiyu Dai, Committee Member
    Breast cancer is the most common malignancy in women and is three times more common than all gynecologic malignancies put together. The incidence of breast cancer has been increasing steadily from an incidence of 1:20 in 1960 to 1:8 women today. Seventy percent of all breast cancers are found through breast self-exams. However not all lumps are detectable by touch and mammography is a low-dose X-ray examination that can detect breast cancer up to two years before it is large enough to be felt. Some patterns of microcalcifications (small white deposits of calcium) give an early indication of cancer. Their small size makes their detection difficult for the radiologist. This brings in the role of CAD (Computer Aided Diagnosis) which serve as an assistant to the radiologist. In this thesis we have investigated the performance of three state of the art CAD techniques for the detection of microcalcifications in mammograms. First, is a wavelet based technique which applies an adaptive wavelet filter to the input mammogram. Then it calculates HOS (Higher Order Statistics) values for maxima locations that are determined from the input image by an empirical method. This is followed by determination of a threshold using a cross entropy based thresholding algorithm. The thresholded image gives the locations of microcalcifications. Second, is a technique that pre-processes the input mammogram with a tophat morphological filter which only preserves objects that are smaller than the size of the filter used in pre-processing. This is again followed by the determination of a threshold using the same thresholding algorithmas in the first technique. The thresholded image indicates the positions of microcalcifications. We have also done an investigation of co-occurrence matrix based entropy thresholding schemes. We found that two dimensional matrix based algorithms perform better than three dimensional based algorithms. Although both fail in case of images with high dynamic range which make them unsuitable for medical imaging. However the cross entropy based method performed better than co-occurrence matrix based techniques for both low as well as high resolution images. Third, is a technique that makes use of a high pass filter for pre-processing. Classification of a location as a microcalcification is done by a SVM (Support Vector Machine) classifier using a scheme called SEL(Successive Enhancement Learning). These techniques have been compared by the use of ROC curves and we found out that the SVM based technique gives the lowest false positives for high detection rate. However cross entropy method does gives lower false positives for detection rates lower than 65%.
  • No Thumbnail Available
    A Prototype Hadamard Imaging System
    (2006-09-07) Fothergill, Daryl William; Dr. John Muth, Committee Chair; Dr. Robert Kolbas, Committee Member; Dr. David Lalush, Committee Member
    The purpose of this thesis was to investigate the possibility of creating an inexpensive imaging system that would be suitable for imaging small animals, either the skin of mice for skin cancer studies, or potentially whole animal imaging. In this optical system the light is collected by an array of 31 optical fibers. In more advanced systems one can envision 1024, or even more fibers being used to increase the resolution of the image. The principle novelty of this system is that Hadamard encoding enabled only one photodetector to be used for the whole system rather than one detector for each fiber. There are two important advantages that can be obtained by using this strategy. First, especially with large numbers of fibers, the overall signal to noise ratio of the system can be improved. Second, the cost and complexity of the system can be greatly reduced. In cases where the signal to noise ratio is low, such as fluorescence detection, designing a system that has only one detector has substantial advantages. This system can also be applied to other sensor applications with large numbers of inputs. To our knowledge Hadamard imaging has not been applied to macroscopic imaging applications, or to small animal imagining. Plastic fiber optics are used to gather and pixilate the spatially dependent inputs from the light source. The optical fibers were then switched on and off using a rotating mask encoded with a Hadamard matrix by drilling holes in the mask. The encoded light was then detected with an inexpensive photodetector and decoded using a desktop computer. The system is automated by using a BASIC Stamp to control the stepper motors and LabVIEW. Future improvements such as a stationary MEMS mask and glass optical fibers that could improve the system by making it more efficient and smaller in size are discussed.