Segmentation of sputum color image for lung cancer diagnosis based on mean shift algorithm

2013 Africon ◽  
2013 ◽  
Author(s):  
Fatma Taher ◽  
Naoufel Werghi ◽  
Hussain Al-Ahmad
Keyword(s):  
Lung Cancer ◽  
Cancer Diagnosis ◽  
Color Image ◽  
Mean Shift ◽  
Mean Shift Algorithm ◽  
Lung Cancer Diagnosis

Computer-Aided Lung Cancer Diagnosis Approaches Based on Deep Learning

2018 ◽  
Vol 30 (1) ◽  
pp. 90 ◽  
Author(s):  
Peng Zhang ◽  
Xinnan Xu ◽  
Hongwei Wang ◽  
Yuanli Feng ◽  
Haozhe Feng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Cancer Diagnosis ◽  
Lung Cancer Diagnosis ◽  
Computer Aided

Biased Lung Cancer Risk Perceptions: Smokers are Misinformed

2018 ◽  
Vol 238 (5) ◽  
pp. 395-421 ◽  
Author(s):  
Nicolas R. Ziebarth
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Cancer Diagnosis ◽  
Mortality Risk ◽  
Risk Perceptions ◽  
Lung Cancer Risk ◽  
Lifetime Risk ◽  
Lung Cancer Diagnosis ◽  
Cancer Risk Perceptions ◽  
Overall Mortality

Abstract This paper empirically investigates biased beliefs about the risks of smoking. First, it confirms the established tendency of people to overestimate the lifetime risk of a smoker to contract lung cancer. In this paper’s survey, almost half of all respondents overestimate this risk. However, 80% underestimate lung cancer deadliness. In reality, less than one in five patients survive five years after a lung cancer diagnosis. Due to the broad underestimation of the lung cancer deadliness, the lifetime risk of a smoker to die of lung cancer is underestimated by almost half of all respondents. Smokers who do not plan to quit are significantly more likely to underestimate this overall mortality risk.

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