MASK-RCNN on the diagnoses of lung cancer in Kurdistan Region of Iraq

Krmanj F. Taher; Abbas M.  Ali; Gullanar M. Hadi

doi:10.21271/ZJPAS.36.1.4

Authors

Krmanj F. Taher Department of Software Engineering and Informatics, College of Engineering, Salahaddin University- Erbil, Kurdistan Region, Iraq
Abbas M. Ali Department of Software Engineering and Informatics, College of Engineering, Salahaddin University- Erbil, Kurdistan Region, Iraq
Gullanar M. Hadi Department of Software Engineering and Informatics, College of Engineering, Salahaddin University- Erbil, Kurdistan Region, Iraq

DOI:

https://doi.org/10.21271/ZJPAS.36.1.4

Keywords:

Lung Cancer, Computer-Aided diagnosis, Deep Learning, Mask-RCNN, CT scan images

Abstract

Cancer is one of the danger diseases in our life, especially lung cancer is one of the most effected organs by cancer and causes death. The early detection of the tumor is very important issue for staging the cancer phases, usually the shape and size of the tumor are considered for classify the cancer type, calculation size of the tumor area and detecting it in accurate way will help to save patient life, this paper uses Mask-RCNN to analyze and detect malignant and benign tumor with real dataset of CT scan lung cancer images in (Kurdistan Region of Iraq) KRI, also develop calculating area size of tumor in cm². After training and testing the system accuracy 96.59%, sensitivity 95%, specificity 95% and F_1 score 99.65% have been achieved. The study concludes that Mask-RCNN is a very good model for diagnoses cancer tumors and can help radiologists to detect and stage the cancer.

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