A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities
CVGIP: Image Understanding
Randomized Hough transform: improved ellipse detection with comparison
Pattern Recognition Letters
Direct Least Square Fitting of Ellipses
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised cell nucleus segmentation with active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Ellipse detection based on symmetry
Pattern Recognition Letters
A new circle/ellipse detector using genetic algorithms
Pattern Recognition Letters
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Cell image segmentation with kernel-based dynamic clustering and an ellipsoidal cell shape model
Computers and Biomedical Research
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Fast Robust GA-Based Ellipse Detection
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Level Set Based Shape Prior Segmentation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Towards recognition-based variational segmentation using shape priors and dynamic labeling
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
A two-level method for segmenting cytological images based on active contour model
Pattern Recognition and Image Analysis
An evolutionary tabu search for cell image segmentation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
Segmentation of Neural Stem/Progenitor Cells Nuclei within 3-D Neurospheres
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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Detection of cell nucleus is critical in microscopy image analysis and ellipse detection plays an important role because most nuclei are elliptical in shapes. We developed an ellipse detection algorithm based on the Mumford-Shah model that inherits its superior properties. In our ellipse detector, the active contours in the Mumford-Shah model are constrained to be non-overlapping ellipses. A quantitative comparison with the randomized Hough transform shows that the Mumford-Shah based approach detects nucleus significantly better on our data sets.