End-to-End Fully Automated Lung Cancer Screening System

Abstract

The computer aided diagnosis of lung cancer is majorly focused on detection and segmentation with very less work reported on volume estimation and grading of cancerous nodule. Further,lung cancer segmentation systems are semi automatic in nature requiring radiologists to demarcatecancerous portions on every slice. This leads to subjectivity and delayed diagnosis. Further, these techniques are based on standard convolution leading to inaccurate segmentation in terms of actual boundary retention of the cancerous nodule.