微衛星DNA的遺傳態品多型條帶上的自動影像資料分析(Aida)，包含自動化的影像分割以及轉換資料為絕對長度。計算的自動化分析在實驗的重製性以及人為的檢驗方面顯得格外重要。為了能在影像上切割出灰階值高低不一的物件，在作物件分割之前，本論文使用兩種不同的方法，分別是peak method以及 window　method來做物件的定位，以達到影像分析的自動化。接下來使用Otsu演算法來作物件分割。切割出來的物件我們稱為條帶，我們從分割後的影像上開始計算每個條帶的統計量，比如條帶的大小，灰階值等等。另外，基於選擇特定的DNA長度標準來計算樣本條帶的長度，會得到浮點數的結果，造成在資料整合上的損失。本論文使用文化大學張春梵老師實驗室自製的DNA長度標準，稱為MarkQoff，即可計算出每個樣本條帶的絕對長度。

Automatic image data analysis (Aida) on the genotyping polymorphic bands of microsatellite DNA requires routinely automatic image segmentation and especially translated absolute data. Computerized automatic analysis is crucial in reproducibility and artifact-proof despite of the available commercial software which is highly interactive and hence gravely time-consuming. Albeit, the genotyping data of microsatellite DNA fragment that is represented as relative mobility sizes with floating points based on selected DNA size standards may lead to great loss in data integration. The implemented Aida system with general-Aida-modules (GAM) of object segmentation and specific-Aida-modules (SAM) of data translation intends to provide efficient solutions in its semi-automatic format. In an experiment of twenty images, the Aida system demonstrated 85~95% accuracy in automatic band segmentation. Moreover, the Aida system along with in-house DNA size standards of MarkQoff (Marker-Quarter-Off) successfully translated absolute size data of DNA fragments with zero standard deviation while analyzing triplicate genotyping images of three running distances. In contrast to Aida system’s superior performance, the results of commercial software based on fifteen DNA size standards in triplicate genotyping images delivered the DNA fragment size data up to 2.19 base pair of standard deviation along with the discrepancies of data floating points and missing bands.

[Adi01] Adiga PSU et al., “Automatic analysis of agarose gel images,” Bioinformatics, 17(11): 1084 - 1090, 2001.
[Akb04] Akbari A and Albregtsen F, “Automatic Segmentation of DNA Bands in One Dimensional Gel Images Produced by Hybridizing Techniques,” Proceedings of the 26th Annual International Conference of the IEEE EMBS(26): 2852 - 2855, 2004.
[App97] Appel RD, Vargas JR, Palagi PM, Walther D, and Hochstrasser DF, “Melanie II - a third-generation software package for analysis of two-dimensional electrophoresis images: II. Algorithms.” Electrophoresis, 18: 2735 - 2748, 1997.
[Baj01] Bajla I, Holländer I, and Burg K, “Improvement of Electrophoretic Gel Image Analysis,” Measurement Science Review, 1(1): 5 - 10, 2001.
[Baj03] Bajla I, Hollander I, and Kollar M, “Novel algorithms implemented in the gel image analysis system GAS2,” Measurement Science Review, 3(2): 57 - 66, 2003.
[Bet96] Bettens E, Scheunders P, Sijbers J, Van DD, and Moens L, “Automatic segmentation and modeling of two-dimensional electrophoresis gels.” International Conference on Image Processing, 2: 665 - 668, 1996.
[Chu84] Church GM and Gilbert W, “Genomic Sequencing,” Proceedings of the National Academy of Sciences of the United States of America-Biological Sciences, 81(7): 1991 - 1995, 1984.
[Cor92] Conradsen K and Pedersen J, “Analysis of two-dimensional electrophoresis gels.” Biometrics, 42: 1273 - 1287, 1992.
[Fuh03] Fuhrmann DR et al., “Software for Automated Analysis of DNA Fingerprinting Gels,” Genome Research, 13: 940 - 953, 2003.
[Job97] Jobling MA, Pandya A, and TylerSmith C, “The Y chromosome in forensic analysis and paternity testing,” International Journal of Legal Medicine, 110(3): 118 - 124, 1997.
[Lin98] Lindeberg T, “Feature Detection with Automatic Scale Selection.” International Journal of Computer Vision, 30: 79 - 116, 1998.
[Mat04] Matsumoto T et al., “Novel algorithm for automated genotyping of microsatellites,” Nucleic Acids Research, 32(20): 6069 - 6077, 2004.
[McC97] McCarthy PJ, Sweetman SFS, McKenna PG and McKelvey M, “Evaluation of manual and image analysis quantification of DNA damage in the alkaline comet assay.” Mutagenesis, 12: 209 - 214, 1997.
[Ots79] Otsu N, "A Threshold Selection Method from Gray-Level Histograms," Journal of IEEE Transactions on Systems, Man, and Cybernetics, SMC(9): 62 - 66, 1979.
[Ste01] Stemmer WPC, “Molecular breeding technology for agriculture and food,” Abstracts of Papers of the American Chemical Society, 221: U32 - U32, 85-AGFD Part 1, 2001.
[Tsa05] Tsai MY, “Gene Expression Computation on Microarray Image Data,” Master Thesis, National Tsing Hua University, 2005.

[Tsa05] Tsai MY, Chang CF, Chu HT, Chan CH, Chang KJ, Kao CY and Chen CC, “Microarray Images Pre-Analysis for Critical Gene Expression Computation with Implemented Algorithmic Kernel.” Hwa Kang Journal of Agriculture, 16: 43 - 50, 2005.
[Ume02] Umeshadiga PS and Chaudhuri BB, “Segmentation and counting of FISH signals in confocal microscopy images.” Micron, 31: 5 - 15, 2000.
[Ume98] Umeshadiga PS and Chaudhuri BB, “An efficient cell segmentation tool for confocal microscopy tissue images for quantitative evaluation of FISH allele bands.” Int. J. Microscopy Res. Techniques, 43: 1 - 20, 1998.
[Ume99] Umeshadiga PS and Chaudhuri BB, “Efficient Cell Segmentation Tool for Confocal Microscopy Tissue Images and Quantitative Evaluation of FISH Signals.” Int. J. Microscopy Res. Technique, 44: 49 - 68, 1999.
[Wat53] Watson JD and Crick FHC, “Molecular Structure of Nucleic Acids,” Nature, 171(4356): 737 - 738, April 25, 1953.
[Web01] http://en.wikipedia.org/wiki/Microsatellite

[Ye99] Ye X et al., “A Recent Development in Image Analysis of Electrophoresis Gels,” Vision Interface, 432 - 438, 1999.
[Zha96] Zhao J, Shimazu Y, Ohta K, Hayasaka R and Matsushita Y, “An outstandingness oriented image segmentation and its application.” Int. Symposium on Signal Processing and its Applications, August, 1996.