A Fog–Cloud Computing-Inspired Image Processing-Based Framework for Lung Cancer Diagnosis Using Deep Learning

2021 ◽  
pp. 19-27
Author(s):  
Aditya Gupta ◽  
Vibha Jain ◽  
Wasaaf Hussain
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Cloud Computing ◽  
Deep Learning ◽  
Cancer Diagnosis ◽  
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

Early-Stage Lung Cancer Diagnosis by Deep Learning-Based Spectroscopic Analysis of Circulating Exosomes

ACS Nano ◽  
2020 ◽  
Vol 14 (5) ◽  
pp. 5435-5444 ◽  
Author(s):  
Hyunku Shin ◽  
Seunghyun Oh ◽  
Soonwoo Hong ◽  
Minsung Kang ◽  
Daehyeon Kang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Cancer Diagnosis ◽  
Spectroscopic Analysis ◽  
Early Stage ◽  
Early Stage Lung Cancer ◽  
Lung Cancer Diagnosis ◽  
Stage Lung Cancer

Deep learning application trial to lung cancer diagnosis for medical sensor systems

2016 ◽  
Author(s):  
Ryota Shimizu ◽  
Shusuke Yanagawa ◽  
Yasutaka Monde ◽  
Hiroki Yamagishi ◽  
Mototsugu Hamada ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Cancer Diagnosis ◽  
Sensor Systems ◽  
Lung Cancer Diagnosis

Naïve Bayes Algorithm for Lung Cancer Diagnosis Using Image Processing Techniques

2017 ◽  
Vol 23 (3) ◽  
pp. 2296-2298 ◽  
Author(s):  
Kusworo Adi ◽  
Catur Edi Widodo ◽  
Aris Puji Widodo ◽  
Rahmat Gernowo ◽  
Adi Pamungkas ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Cancer Diagnosis ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Image Processing Techniques ◽  
Lung Cancer Diagnosis ◽  
Bayes Algorithm ◽  
Processing Techniques

Research on CT Scan Image of Lung Cancer Based on Deep Learning Method in Artificial Intelligence Field

2020 ◽  
Vol 10 (4) ◽  
pp. 934-939
Author(s):  
Xiaochen Yi ◽  
Zongze Sun ◽  
Baolong Yu ◽  
Munan Yang ◽  
Zhuo Zhang
Keyword(s):  
Artificial Intelligence ◽  
Lung Cancer ◽  
Deep Learning ◽  
Cancer Diagnosis ◽  
Lung Nodule ◽  
Three Dimensional ◽  
Image Data ◽  
Heat Map ◽  
Lung Cancer Diagnosis ◽  
Nodule Detection

Cancer is one of the diseases with high mortality in the 21st century, and lung cancer ranks first in all cancer morbidity and mortality. In recent years, with the rise of big data and artificial intelligence, lung cancer-assisted diagnosis based on deep learning has gradually become A popular research topic. Computer-aided lung cancer diagnosis technology is mainly the process of processing and analyzing the lung image data obtained by medical instrument imaging. The process is summarized into four steps: medical image data preprocessing, lung parenchymal segmentation, lung Nodule detection and segmentation, as well as lesion diagnosis. In order to solve the problem that the two-dimensional image model is not applicable to three-dimensional images, this paper proposes a three-dimensional convolutional neural network model suitable for lung cancer diagnosis. The model consists of two parts. The first part is a three-dimensional deep nodule detection network (FCN) model, which generates a heat map of the lung nodules. We can locate the locations of those malignant nodules through the heat map. According to the heat map generated in the first part, the second part selects those malignant nodules that are likely to be large, and then fuses the features of these selected nodules into one feature vector, showing the whole lung scan. Finally, we use this feature to classify and determine whether we have lung cancer.

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