Unsupervised cell nucleus segmentation with active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
Shape Analysis and Classification: Theory and Practice
Shape Analysis and Classification: Theory and Practice
Simulation toolbox for 3D-FISH Spot-counting algorithms
Real-Time Imaging
A fast algorithm for level set-like active contours
Pattern Recognition Letters
A comparison of fast level set-like algorithms for image segmentation in fluorescence microscopy
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Generation of synthetic image datasets for time-lapse fluorescence microscopy
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
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In recent years many various biomedical image segmentation methods have appeared. Though typically presented to be successful the majority of them was not properly tested against ground truth images. The obvious way of testing the quality of new segmentation was based on visual inspection by a specialist in the given field. The novel 3D biomedical image data simulator is presented in this paper. It offers the results of high quality. The comparison of generated synthetic data is compared against real image data using standard similarity techniques.