M.Ing. (Electrical and Electronic Engineering) / Advances in bio-imaging have triggered the development of a highly sophisticated imaging tool known as fluorescence microscopy. Fluorescence microscopy is used in many biological applications to visualize sub-cellular processes and gives the ability to image three-dimensional (3D) structures in living cells. The use of fluorescence microscopy and specific staining methods make biological molecules appear as bright spots in image data. The analysis of fluorescence microscopy images requires the detection and tracking of hundreds spots in image data and is of great importance for biologists to better understand cell functions. However, the analysis of these data is still performed manually in most biological laboratories worldwide. The manual analysis of these data is both time consuming, laborious and susceptible to human errors. Several computer-based algorithms have been proposed for the detection and tracking of spots in microscopy images. Most of these methods were validated on limited image data and relatively few studies have been performed for the comparison of these methods in real applications. This study quantitatively compared the performance of four detection and two tracking methods applied in microscopy images for the analysis of bright spots. The performance of the algorithms was validated on both synthetic and real images. The synthetic images offered a better way of validating algorithms against ground truth reference results. Results indicate that there are major differences in algorithm performance for both detection and tracking. In the detection results the Isotropic Undecimated Wavelet Transform (IUWT) and the Laplacian of Gaussian (LoG) achieved better results than the other methods in comparison when values are considered. The tracking results indicate that the Interacting Multiple Model (IMM) method achieved better results than the Feature Point Tracking (FPT) method when Jaccard Similarity Scores (JSC) are considered.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:11236 |
| Date | 29 May 2014 |
| Creators | Mabaso, Matsilele Aubrey |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
| Rights | University of Johannesburg |
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