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Title Page
Quantitative Description and Automated Classification of Cellular Protein Localization Patterns in Fluorescence Microscope Images of Mammalian Cells
Title Page
Abstract
Acknowledgements
Contents
List of Tables
List of Figures
Introduction
Biological Background
Goals
Motivation
Current State of Protein Localization
Related Work
Fluorescence Microscopy
Pattern Recognition
Choice of Classifiers
Classification Trees
Back-Propagation Neural Networks
k-Nearest Neighbor Classifiers
Confidence Intervals
A Five Class Problem
Introduction
Materials and Methods
Fluorescence Microscopy
Image Processing
Zernike Features
Haralick texture features
Feature Selection
Classification
Reconstruction from Zernike Moments
Results
Image Collection and Processing
Zernike Feature Extraction and Image Reconstruction
Classification Using Zernike Features
Classification Using Haralick Texture Features
Feature Selection and Reduction of Classifier Complexity
Reduced Classifier Complexity
Discussion
A Ten Class Problem
Introduction
Materials and Methods
Fluorescence Microscopy
Image Processing
Zernike Features
Haralick texture features
ad hoc
features
Features Calculated Using Only the Protein Localization Image
Features Calculated Using Both the DNA and Protein Localization Images
Features Calculated Using the Convex Hull of the Protein Fluorescence
Feature Selection
Back-Propagation Neural Network
k-Nearest Neighbor Method
Results
Image Collection and Processing
Feature Extraction
Zernike and Haralick Features
ad hoc
Features
Classification with All Features
Classification with the
ad hoc
Features
Classification with the ``best'' Features
Classification Without a DNA Image
Classification of Images at Lower Resolution
Classification of
Sets
of Images
Discussion
Conclusions
Impact of this Work
Future Work
Applications
Bibliography
Source Code
Image Processing
HeLa Data
mb_tclread.cpp
mb_imgbgsub.m
mb_imgcommonpixel.m
mb_threshcrop.m
mb_imgconvhull.m
mb_nihscale.m
mb_nihthreshold.m
mb_imgscale.m
mb_imgshift.m
mb_imgproc.m
mb_imgcrop.m
Feature Extraction - Zernike
CHO Data
zernike.cpp
zernike.h
cell.cpp
cell.h
object.cpp
object.h
moments.cpp
moments.h
HeLa Data
mb_zernike.m
mb_Znl.cpp
Feature Extraction - Haralick
CHO Data
kharalick
HeLa Data
mb_texture.c
cvip_pgmtexture.c
Feature Extraction -
ad hoc
mb_imgfeatures.pl
mb_imgfeatures.m
mb_imgmoments.m
mb_hullfeatures.m
mb_imgcentmoments.m
mb_imgedgefeatures.m
Back-Propagation Neural Network
CHO Data
HeLa Data
mb_mlptrainstoptest.m
mb_mlptraintest.m
mb_mlptrain.m
mb_mlpthresh.m
mb_mlpconfmatall.m
mb_mlpconfmat.m
mb_mlpclasssummary.m
mb_featurenorm.m
Classificaiton of Sets
mb_mlptrainstoptestsets.m
mb_mlpsets.m
mb_mlpsetsummary.m
k-Nearest Neighbor Classifier
mb_knntrainpicktest.m
mb_knnbestk.m
mb_knn.m
mb_knnsummary.m
About this document ...
Copyright ©1999 Michael V. Boland
1999-09-18
