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IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Parallel marker-based image segmentation with watershed transformation
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ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Level Set Evolution without Re-Initialization: A New Variational Formulation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Convex Grouping Combining Boundary and Region Information
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Color Image Segmentation for Objects of Interest with Modified Geodesic Active Contour Method
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Rapid and Brief Communication: GACV: Geodesic-Aided C-V method
Pattern Recognition
WaterBalloons: A hybrid watershed Balloon Snake segmentation
Image and Vision Computing
Automatic Image Analysis of Histopathology Specimens Using Concave Vertex Graph
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
A geometric active contour model without re-initialization for color images
Image and Vision Computing
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
International Journal of Applied Mathematics and Computer Science - Applied Image Processing
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
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Computers in Biology and Medicine
A new preprocessing approach for cell recognition
IEEE Transactions on Information Technology in Biomedicine
Unsupervised segmentation based on robust estimation and color active contour models
IEEE Transactions on Information Technology in Biomedicine
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Histology image analysis for carcinoma detection and grading
Computer Methods and Programs in Biomedicine
Computer-aided techniques for chromogenic immunohistochemistry: Status and directions
Computers in Biology and Medicine
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Manual assessment of estrogen receptors' (ER) status from breast tissue microscopy images is a subjective, time consuming and error prone process. Automatic image analysis methods offer the possibility to obtain consistent, objective and rapid diagnoses of histopathology specimens. In breast cancer biopsies immunohistochemically (IHC) stained for ER, cancer cell nuclei present a large variety in their characteristics that bring various difficulties for traditional image analysis methods. In this paper, we propose a new automatic method to perform both segmentation and classification of breast cell nuclei in order to give quantitative assessment and uniform indicators of IHC staining that will help pathologists in their diagnostic. Firstly, a color geometric active contour model incorporating a spatial fuzzy clustering algorithm is proposed to detect the contours of all cell nuclei in the image. Secondly, overlapping and touching nuclei are separated using an improved watershed algorithm based on a concave vertex graph. Finally, to identify positive and negative stained nuclei, all the segmented nuclei are classified into five categories according to their staining intensity and morphological features using a trained multilayer neural network combined with Fisher's linear discriminant preprocessing. The proposed method is tested on a large dataset containing several breast tissue images with different levels of malignancy. The experimental results show high agreement between the results of the method and ground-truth from the pathologist panel. Furthermore, a comparative study versus existing techniques is presented in order to demonstrate the efficiency and the superiority of the proposed method.