scholarly journals Review: On Segmentation of Nodules from Posterior and Anterior Chest Radiographs

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
S. K. Chaya Devi ◽  
T. Satya Savithri
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Cancer Detection ◽  
Chest Radiography ◽  
Literature Survey ◽  
Radiographic Images ◽  
Anatomical Structures ◽  
The Past ◽  
The World ◽  
Lung Cancer Detection

Lung cancer is one of the major types of cancer in the world. Survival rate can be increased if the disease can be identified early. Posterior and anterior chest radiography and computerized tomography scans are the most used diagnosis techniques for detecting tumor from lungs. Posterior and anterior chest radiography requires less radiation dose and is available in most of the diagnostic centers and it costs less compared to the remaining diagnosis techniques. So PA chest radiography became the most commonly used technique for lung cancer detection. Because of superimposed anatomical structures present in the image, sometimes radiologists cannot find abnormalities from the image. To help radiologists in diagnosing tumor from PA chest radiographic images range of CAD scheme has been developed for the past three decades. These computerized tools may be used by radiologists as a second opinion in detecting tumor. Literature survey on detecting tumors from chest graphs is presented in this paper.

Lung Cancer Detection Using Deep Convolutional Neural Network

2021 ◽  
Vol 11 (4) ◽  
pp. 13-20
Author(s):  
Syed Farhan Hyder Abidi ◽  
Sumukhi T. ◽  
Vinod Kumar H. ◽  
Santhosh B.
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Lung Cancer ◽  
Early Detection ◽  
Convolutional Neural Network ◽  
Cancer Detection ◽  
Neural System ◽  
Malignant Growth ◽  
The World ◽  
Lung Cancer Detection

Lung malignant growth is one of the most threatening ailments affecting most of the nations in the world, and detection in earlier stages has been a challenge. Early detection can help in saving many lives. This paper shows a methodology that uses a convolutional neural network (CNN) in machine learning for the detection of tumours in the lung. The specificity of the model is desirable and dependable and increasingly productive in contrast to the accuracy shown by conventional neural system frameworks.

scholarly journals Multistage Lung Cancer Detection and Prediction Using Deep Learning

2021 ◽  
pp. 54-60
Author(s):  
Jay Jawarkar ◽  
Nishit Solanki ◽  
Meet Vaishnav ◽  
Harsh Vichare ◽  
Sheshang Degadwala
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Lung Injury ◽  
Cancer Detection ◽  
Social Affair ◽  
The World ◽  
Primary Driver ◽  
Onset Period ◽  
Lung Cancer Detection ◽  
Basic Learning

Earlier, the progression of the descending lung was the primary driver of the chaos that runs across the world between the two people, with more than a million people dies per year goes by. The cellular breakdown in the lungs has been greatly transferred to the inconvenience that people have looked at for a very predictable amount of time. When an entity suffers a lung injury, they have erratic cells that clump together to form a cyst. A dangerous tumor is a social affair involving terrifying, enhanced cells that can interfere with and strike tissue near them. The area of lung injury in the onset period became necessary. As of now, various systems that undergo a preparedness profile and basic learning methodologies are used for lung risk imaging. For this, CT canal images are used to see and save the adverse lung improvement season from these handles. In this paper, we present an unambiguous method for seeing lung patients in a painful stage. We have considered the shape and surface features of CT channel pictures for the sales. The perspective is done using undeniable learning methodologies and took a gender at their outcome.

Green synthesis of nanomaterials for early lung cancer detection

2018 ◽  
pp. 1-1
Keyword(s):  
Lung Cancer ◽  
Green Synthesis ◽  
Cancer Detection ◽  
World Wide ◽  
Early Stage ◽  
Age Groups ◽  
Early Lung Cancer ◽  
Lung Cancer Detection ◽  
Synthesis Of Nanomaterials

Lung cancer is the foremost cause of cancer-related deaths world-wide [1]. It affects 100,000 Americans of the smoking population every year of all age groups, particularly those above 50 years of the smoking population [2]. In India, 51,000 lung cancer deaths were reported in 2012, which include 41,000 men and 10,000 women [3]. It is the leading cause of cancer deaths in men; however, in women, it ranked ninth among all cancerous deaths [4]. It is possible to detect the lung cancer at a very early stage, providing a much higher chance of survival for the patients.

Sign in / Sign up

Export Citation Format

Share Document