Lungs Cancer Detection Using Digital Image Processing Techniques: A Review

  • Muti ullah Department of Computer Science, National College of Business Administration and Economics, Bahawalpur , Pakistan
  • Mehwish  Bari Department of Mathematics, National College of Business Administration and Economics, Bahawalpur , Pakistan
  • Adeel  Ahmed Department of Computer Science, Quaid-e-Azam University, Islamabad, Pakistan.
  • Sajid  Naveed Department of Computer Science, National College of Business Administration and Economics , Bahawalpur , Pakistan


From last decade, lung cancer become sign of fear among the people all over the world. As a result, many countries generate funds and give invitation to many scholars to overcome on this disease. Many researchers proposed many solutions and challenges of different phases of computer aided system to detect the lung cancer in early stages and give the facts about the lung cancer. CV (Computer Vision) play vital role to prevent lung cancer. Since image processing is necessary for computer vision, further in medical image processing there are many technical steps which are necessary to improve the performance of medical diagnostic machines. Without such steps programmer is unable to achieve accuracy given by another author using specific algorithm or technique. In this paper we highlight such steps which are used by many author in pre-processing, segmentation and classification methods of lung cancer area detection. If pre-processing and segmentation process have some ambiguity than ultimately it effects on classification process. We discuss such factors briefly so that new researchers can easily understand the situation to work further in which direction.

Apr 1, 2019
How to Cite
ULLAH, Muti et al. Lungs Cancer Detection Using Digital Image Processing Techniques: A Review. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 38, n. 2, p. 351-360, apr. 2019. ISSN 2413-7219. Available at: <>. Date accessed: 18 apr. 2019.
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License