Developement of computer aided system for detection and classification of mitosis using SVM

@article{Amitha2017DevelopementOC,
  title={Developement of computer aided system for detection and classification of mitosis using SVM},
  author={Hegde Amitha and I. Selvamani and Dr. D. Anto Sahaya Dhas},
  journal={2017 International Conference on Inventive Computing and Informatics (ICICI)},
  year={2017},
  pages={954-958}
}
In modern medicine, digital pathology represents one of the major and challenging research field. Pathological exams have a critical role in diagnosis process. Histopathological grading of breast cancer provides prior knowledge to the patients prognosis and helps to make further treatment plans. But, manual analysis of numerous biopsy slides is a labor-intensive work for pathologists. In the case of breast cancer grading, Nottingham grading system (NGS) is the standard. Tubule formation… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 15 REFERENCES

Automated mitosis detection with deep regression networks

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
  • 2016

Bilgin,”Mitosis detection using convolutional neural network based features,

G. A. Albayrak
  • IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI),
  • 2016
VIEW 3 EXCERPTS

Heng,”Automated mitosis detection with deep regression networks,

H. Chen, P.A.X. Wang
  • IEEE 13th International Symposium on Biomedical Imaging (ISBI),Prague,pp
  • 2016
VIEW 3 EXCERPTS

Ghassemian,”Automated mitosis detection based on combination of effective textural and morphological features from breast cancer histology slide images,

H. F. Pourakpour
  • 22nd Iranian Conference on Biomedical Engineering (ICBME), Tehran,,pp
  • 2015
VIEW 2 EXCERPTS