LUNG CANCER DETECTION USING CNN

LUNG CANCER DETECTION USING CNN

Pritish Chepure¹, Prathamesh Chavan, Avinash pawar³ , Prof.Dhanashri Londhe

¹Computer Department,Shree Ramchandra College Of Enginerring

² Computer Department,Shree Ramchandra College Of Enginerring

 ³ Computer Department,Shree Ramchandra College Of Enginerring

Abstract — The results of the National Lung Screening Trial, which suggested reduced mortality in high-risk subjects undergoing CT screening, sparked discussion about establishing a lung cancer screening programme. Important questions about the benefit-harm balance, as well as the specifics of a screening program's cost-effectiveness, remain unanswered. A group of experts chest radiology, respiratory medicine, and epidemiology experts Following several meetings, representatives from cardiology and thoracic surgery from all Swiss university hospitals drafted this joint statement. The panel claims that the introduction of a lung cancer virus is uncontrolled and premature.nThe screening programme could result in long-term harm.Without strict quality control, undetectable. This position statement focuses on the requirements for running a programme like this with the the goal of coordinating efforts across the board The underlying statement contains information on current evidence for lung cancer screening reducing mortality, as well as the epidemiologic implications of such a programme in Switzerland. There are also requirements for lung cancer screening centres, as well as recommendations for both the CT technique and the lung cancer screening algorithm. Nodule evaluations are available. Furthermore, related issues such as The topics of patient management, registry, and funding are all covered. Based on based on current knowledge, the panel concludes that lung In Switzerland, cancer screening should be done exclusively. within the context of a national observational study to provide answers to Before considering broad population-based data, there are a few key questions to consider.lung cancer examination.

Keywords:- CNN , Preprocessing, Feature Extraction.