HEART DISEASES CLASSIFICATION AND FEATURE EXTRACTION BY SEGMENTATION AND MACHINE LEARNING MODEL

Authors

  • V. Appala Raju Vignan’s Institute of Information Technology (A), Duvvada, Visakhapatnam, Andhra Pradesh, Author
  • G Indira Devi Assistant Professor Department of ECM, Vignan’s Institute of Information Technology (A), Duvvada, Visakhapatnam, Andhra Pradesh, India, Author
  • A.Sampath Dakshina Murthy assistant Professor Department of ECE, Vignan’s Institute of Information Technology (A), Duvvada, Visakhapatnam, Andhra Pradesh, India Author
  • K. Saikumar Research Scholar, Department of ECE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India, Author
  • B. Omkar Lakshmi Jagan Research Scholar, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India, Author

DOI:

https://doi.org/10.61841/0tcxa634

Keywords:

Parasternal Long Axis, ultra-scan,, middle channel, , optical stream,, heart diseases classification.

Abstract

The heart is one of the major organ part that stimulatesthe blood pressure for body parts. If this heart has damaged by any diseases or infections than automatically, the body parts are inflicted. Heart diagnosis is mainly possible by MRI scan, Ultra scan and ECG machine analysis. In this research work, coronary heart diseases are identified using ultrasound imaging process. For this segmentation, feature extraction and classification has performed by advanced methodologies. This work is most useful for researchers and doctors for easy of diagnosis the heart diseases. At final calculating the performance measures i.e. Recall, F1 score, True positive rate and efficiency. Outputs are challenging the existed models and increasing the accuracy at diagnosis of the heart.

Downloads

Download data is not yet available.

References

1. Sigit, Riyanto, Tri Harsono, and Baiq Herawati Aisyah Noor. "Heart video tracking system on long axis view." In 2016 International Electronics Symposium (IES), pp. 271-276. IEEE, 2016.

2. Pratiwi, Arvina Aulia, Riyanto Sigit, Dwi Kurnia Basuki, and Yudi Her Oktaviono. "Improved ejection fraction measurement on cardiac image using optical flow." In 2017 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCIC), pp. 295-300. IEEE, 2017.

3. Sigit, Riyanto, Ali Ridho Barakbah, I. A. Sulistiono, and I. A. S. Aziz. "Automatic cardiac segmentation using triangle and optical flow." Indonesian Journal of Electrical Engineering and Computer Science 8, no. 2 (2017): 315-326.

4. Sundaramurthy, S., Amithab Wahi, L. Priyanga Devi, and S. Yamuna. "Cardiac Cycle Phase Detection in Echocardiography Images Using ANN." In 2014 International Conference on Intelligent Computing Applications, pp. 275-279. IEEE, 2014.

5. Sigit, Riyanto, and Eva Rochmawati. "Segmentation echocardiography video using B-Spline and optical flow." In 2016 International Conference on Knowledge Creation and Intelligent Computing (KCIC), pp. 226-231. IEEE, 2016.

6. Farnebäck, Gunnar. "Two-frame motion estimation based on polynomial expansion." In Scandinavian conference on Image analysis, pp. 363-370. Springer, Berlin, Heidelberg, 2003.

7. Saikumar, K., and V. Rajesh. "Coronary blockage of artery for Heart diagnosis with DT Artificial Intelligence Algorithm." International Journal of Research in Pharmaceutical Sciences11, no. 1 (2020): 471-479.

8. Dr. B. Sankara babu, A. Sampath Dakshina Murthy, Sampenga Veerraju, B. Omkar Lakshmi Jagan , K. Saikumar “Implementation of Real and Accurate Watermarking System For Security Using Logistic

Regression Machine Learning Techniques”, The Journal of Research on the Lepidoptera, Volume 51 (1): 783-792, March 2020.

9. A. Sampath Dakshina Murthy, P. Satyanarayana Murthy, V. Rajesh, Sk. Hasane Ahammad, B. Omkar Lakshmi Jagan, “Execution of Natural Random Forest Machine Learning Techniques on Multi Spectral Image Compression”, International Journal of Pharmaceutical Research Volume 11, Issue 4, Oct - Dec, 2019.

10. K.Raju, S.Kiran Pilli, G. Siva Suresh Kumar, K. Saikumar, B. Omkar Lakshmi Jagan, “Implementation of Natural Random Forest Machine Learning Methods on Multi Spectral Image Compression”, Journal of Critical Review, Volume 6, Issue 5, pg. 265-273, 2019.

11. Ravada Aamani, Adinarayana Vannala, A. Sampath Dakshina Murthy, K. Saikumar, B. Omkar Lakshmi Jagan, “Heart Disease Diagnosis Process using MRI Segmentation And Lasso Net Classification ML”, Journal of Critical Review, Volume 7, Issue 6, pg. 717-721, 2020.

Downloads

Published

30.06.2020

How to Cite

Raju, V. A., Devi, G. I. ., Murthy, A. D. ., Saikumar, K. ., & Jagan, B. O. L. . (2020). HEART DISEASES CLASSIFICATION AND FEATURE EXTRACTION BY SEGMENTATION AND MACHINE LEARNING MODEL. International Journal of Psychosocial Rehabilitation, 24(6), 8992-9001. https://doi.org/10.61841/0tcxa634