IT 10 027
Examensarbete 15 hp June 2010
Nuclei segmentation on bright-field images
Francisco Cruz Fernández
Teknisk- naturvetenskaplig fakultet UTH-enheten
Besöksadress:
Ångströmlaboratoriet Lägerhyddsvägen 1 Hus 4, Plan 0 Postadress:
Box 536 751 21 Uppsala Telefon:
018 – 471 30 03 Telefax:
018 – 471 30 00 Hemsida:
http://www.teknat.uu.se/student
Abstract
Nuclei segmentation on bright-field images
Francisco Cruz Fernández
Nuclei segmentation is a common and complicated task in image analysis. There is no general solution for the problem, and depending on the image characteristics the segmentation can be performed in different ways. Bright-field images add some complications to the problem; the color of some elements of the image is close to the color of the nuclei, making the segmentation difficult. In this thesis some methods are presented to complete this task, two classifiers, minimum distance classifier and multilayer perceptron are tested to enhance the nuclei. After the classification, threshold methods together with morphological operations are used to get the segmentation of the nuclei with an accuracy around 85%.
Examinator: Anders Jansson Ämnesgranskare: Amin Allalou Handledare: Amin Allalou
Contents
Abstract
1. Introduction……… 4
1.1. Overview………...……… 4
1.2. Project aim……… 4
2. Background Theory...….………. 5
2.1. Digital Image analysis………. 5
2.2. Previous work………... 5
2.3. Used tools... 6
2.4. Algorithms and operations... 6
2.4.1. Segmentation... 7
2.4.2. Median Filter... 8
2.4.3. Minimum distance classifier... 8
2.4.4. Neural Networks: Multilayer Perceptron... 9
2.4.5. Threshold: Otsuʼs Method... 11
2.4.6. Bilinear Interpolation... 12
2.4.7. Morphological operations... 13
3. Materials and Methods...14
3.1. Image acquisition... 14
3.2. Image set... 14
3.3. Classifying nuclei by minimum distance... 15
3.4. Multilayer perceptron classification... 16
3.5. Threshold... 20
3.6. Morphological operations... 22
4. Results...24
5. Conclusions... 28
6. Future Work...28
6. Acknowledgments... 28
8. References... 29
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