Automated Cancer Detection and Classification

Authors

  • Arsya Sinatria Artha Sekolah Tunas Mekar Indonesia, Lampung, Indonesia
  • Andino Maseleno International Open University, Gambia
  • Aa Hubur International Open University, Gambia

DOI:

https://doi.org/10.38035/dhps.v2i2.1811

Keywords:

Detection, Cancer, Image Processing, Segmentation, Hybrid Approach

Abstract

Detection of cancer is very difficult and need more concern in the field of medical. This paper studies the various causes, types, symptoms of cancer. The main objective of this paper is to design an efficient and effective approach to detect the cancer using image processing. The research proposed an improved hybrid approach for detection and segmentation. The research work includes improvement of microscopic image, then segmentation of cells, extract the features of cancer and then at the final stage it described the classification step.  After using different approaches and review several previous approaches this technique used an efficient and appropriate method to design a proposed framework.

References

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Published

2025-04-21

How to Cite

Artha, A. S., Maseleno, A., & Hubur, A. (2025). Automated Cancer Detection and Classification. Dinasti Health and Pharmacy Science, 2(2), 51–58. https://doi.org/10.38035/dhps.v2i2.1811

Issue

Vol. 2 No. 2 (2024): Dinasti Health and Pharmacy Science (October 2024)

Section

Articles

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Copyright (c) 2025 Arsya Sinatria Artha, Andino Maseleno, Aa Hubur

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