Detection of Cancer Cells in Human Blood Samples Using Microscopic Images

Authors

  • Piruthiviraj P  Department of ECE, New Horizon College of Engineering, Bangalore, India
  • M Rishi  Department of ECE, New Horizon College of Engineering, Bangalore, India
  • P Sree Raj  Department of ECE, New Horizon College of Engineering, Bangalore, India
  • Sai Hasan  Department of ECE, New Horizon College of Engineering, Bangalore, India
  • Chetan Kumar  Department of ECE, New Horizon College of Engineering, Bangalore, India
  • VMV Mahesh Babu  Department of ECE, New Horizon College of Engineering, Bangalore, India

Keywords:

Blood cell, abnormal cell, Image processing, Image segmentation, Image enhancement, Thresholding techniques.

Abstract

Blood testing is now widely regarded as one of the most important clinical examinations. A blood cell's characteristics (volume, shape, and color) might reveal vital information about a patient's health. On the other hand, inspection process takes time and requires a high level of expertise knowledge. As a result, automated medical diagnosis technologies are needed to help clinicians identify illnesses promptly and reliably. The main objective of normal blood segmentation is just to isolate defective/abnormal units from a complex background and segments them into architectural elements utilizing image processing techniques such as contrast enhancement, thresholding, and morphological procedures, among others. The suggested method here reduces noise and enhances visual segmentation. All previous methods used different segmentation strategies, which resulted in less efficiency than the suggested method. This work can be implemented using MATLAB environment.

References

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Published

2022-06-30

Issue

Section

Research Articles

How to Cite

[1]
Piruthiviraj P, M Rishi, P Sree Raj, Sai Hasan, Chetan Kumar, VMV Mahesh Babu "Detection of Cancer Cells in Human Blood Samples Using Microscopic Images" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 3, pp.737-745, May-June-2022.