Ilastik: Interactive learning and segmentation toolkit

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2011, Pages 230-233

  Sommer, Christoph ^a   Straehle, Christoph ^a   Kothe, Ullrich ^a   Hamprecht, Fred A ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

image segmentation; Interactive classification; machine learning; software tools

Indexed keywords

DIGITAL IMAGE; HIGH-CONTENT; INTERACTIVE CLASSIFICATION; INTERACTIVE LEARNING; MACHINE-LEARNING; MULTI-CORE MACHINES; MULTI-THREADING; OPEN SOURCE PROJECTS; RANDOM FOREST CLASSIFIER; REAL TIME PERFORMANCE; REAL-TIME FEEDBACK; SEGMENTATION RESULTS; SOFTWARE TOOL; SPECTRAL DIMENSIONS; UNCERTAINTY MEASURES;

DECISION TREES; EMBEDDED SYSTEMS; LEARNING SYSTEMS; MACROS; MAMMALS; MEDICAL IMAGING; USER INTERFACES;

IMAGE SEGMENTATION;

EID: 79961198540     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2011.5872394     Document Type: Conference Paper

References (16)

1. A. E. Carpenter, T. R. Jones, M. R. Lamprecht, C. Clarke, I. H. Kang, O. Friman, D. A. Guertin, J. H. Chang, R. A. Lindquist, J. Moffat, P. Golland, and D. M. Sabatini, "CellProfiler: image analysis software for identifying and quantifying cell pheno-types," Genome Biol., vol. 7, pp. R100, 2006.
2. R. Adams and L. Bischof, "Seeded region growing," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, pp. 641-647, 1994.
3. L. Grady, "Random walks for image segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1768-1783, 2006.
4. C. Rother, V. Kolmogorov, and A. Blake, "Grabcut: Interactive foreground extraction using iterated graph cuts," ACM Trans. Graph., vol. 23, no. 3, pp. 309-314, 2004.
5. Y. Boykov and M.-P. Jolly, "Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images," ICCV'01, vol. 1, pp. 105-112, 2001.
6. G. Friedland, K. Jantz, and R. Rojas, "SIOX: Simple interactive object extraction in still images," in Seventh IEEE International Symposium on Multimedia, 2005.
7. X. Bai and G. Sapiro, "A geodesic framework for fast interactive image and video segmentation and matting," in IEEE 11th International Conference on Computer Vision, 2007, pp. 1-8.
8. B.L. Price, B. Morse, and S. Cohen, "Geodesic graph cut for interactive image segmentation," in Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. IEEE, 2010, pp. 3161-3168.
9. L. Breiman, "Random forests," Machine Learning, vol. 45, pp. 5-32, 2001.
10. M. Jehle, C. Sommer, and B. Jähne, "Learning of optimal illumination for material classification," in Pattern Recognition. 2010, pp. 563-572, Springer.
11. A. Hoover, V. Kouznetsova, and M. Goldbaum, "Locating blood vessels in retinal images by piece-wise threshold probing of a matched filter response," IEEE Trans. on Medical Imaging, vol. 19, no. 3, pp. 203-210, 2000.
12. B Soares, G. Leandro, M. Cesar, F. Jelinek, and J. Cree, "Retinal vessel segmentation using the 2-d gabor wavelet and supervised classification," IEEE Trans. on Medical Imaging, vol. 25, no. 9, pp. 1214-1222, 2006.
13. S. Chaudhuri, S. Chatterjee, N. Katz, M. Nelson, and M. Goldbaum, "Detection of blood vessels in retinal images using two-dimensional matched filters," IEEE Trans. on Medical Imaging, vol. 8, no. 3, pp. 263-269, 1989.
14. X Jiang and D. Mojon, "Adaptive local thresholding by verification-based multi threshold probing with application to vessel detection in retinal images," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 25, no. 1, pp. 131-137, 2003.
15. J. Staal, M. D. Abramoff, M. Niemeijer, M. A. Viergever, and B. van Ginneken, "Ridge-based vessel segmentation in color images of the retina," IEEE Trans. on Medical Imaging, vol. 23, no. 4, pp. 501-509, 2004.
16. J. Moffat and et al., "A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen," Cell, vol. 124, no. 6, pp. 1283-1298, 2006.