Segmentation of nuclei from breast histopathology images using PSO-based Otsu’s multilevel thresholding

Advances in Intelligent Systems and Computing

Volumn 325, Issue , 2015, Pages 835-843

  Angel Arul Jothi, J ^a   Mary Anita Rajam, V ^a  

^a ANNA UNIVERSITY   (India)

Author keywords

Automated histopathology; Computer aided diagnosis; Hepatocellular carcinoma; Otsu s multilevel thresholding; Particle swarm optimization

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER AIDED ANALYSIS; IMAGE SEGMENTATION; MEDICAL IMAGING; PARTICLE SWARM OPTIMIZATION (PSO);

AUTOMATED HISTOPATHOLOGY; DISCRIMINANT CRITERIA; HEPATOCELLULAR CARCINOMA; MULTILEVEL THRESHOLDING; OBJECTIVE FUNCTIONS; OPTIMAL THRESHOLD; OPTIMIZATION PROBLEMS; THRESHOLD SELECTION;

COMPUTER AIDED DIAGNOSIS;

EID: 84912571605     PISSN: 21945357     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-81-322-2135-7_88     Document Type: Conference Paper

References (9)

1. P.-W. Huang, Y.-H. Lai, Effective segmentation and classification for HCC biopsy images. Pattern Recogn. 43(4), 1550–1563 (2010)
2. Y. Al-Kofahi, W. Lassoued, W. Lee, B. Roysam, Improved automatic detection and segmentation of cell nuclei in histopathology images. IEEE Trans. Biomed. Eng. 57(4), 841–852 (2010)
3. M.M. Dundar, S. Badve, G. Bilgin, V. Raykar, R. Jain, O. Sertel, M.N. Gurcan, Computerized classification of intraductal breast lesions using histopathological images. IEEE Trans. Biomed. Eng. 58(7), 1977–1984 (2011)
4. C. Lu, M. Mahmood, N. Jha, M. Mandal, A robust automatic nuclei segmentation technique for quantitative histopathological image analysis. Anal. Quant. Cytol. Histol. 34(6), 296–308 (2012)
5. M. Veta, P.J. van Diest, R. Kornegoor, A. Huisman, M.A. Viergever, J.P.W. Pluim, Automatic nuclei segmentation in H&E stained breast cancer histopathology images. PLoS ONE 8(7), e70221 (2013)
6. P. Ghamisi, M.S. Couceiro, J.A. Benediktsson, M.F. Nuno, N.M. Ferreira, An efficient method for segmentation of images based on fractional calculus and natural selection. Expert Syst. Appl. 39(16), 12407–12417 (2012)
7. R.V. Kulkarni, G.K. Venayagamoorthy, Bio-inspired algorithms for autonomous deployment and localization of sensor nodes. IEEE Trans. Syst., Man, Cybern. 40(6), 663–675 (2010)
8. E.D. Gelasca, J. Byun, B. Obara, B.S. Manjunath, Evaluation and benchmark for biological image segmentation, in IEEE International Conference on Image Processing (2008)
9. N. Otsu, A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)