Computer aided detection system for lung cancer using computer tomography scans

2018 ◽  
Author(s):  
Shanthi Mahesh ◽  
Spoorthi Rakesh ◽  
Vidya C. Patil
Keyword(s):  
Lung Cancer ◽  
Computer Tomography ◽  
Detection System ◽  
Computer Aided Detection ◽  
Computer Aided

Use of a Computer-aided Detection System to Detect Missed Lung Cancer at Chest Radiography

Radiology ◽  
2009 ◽  
Vol 252 (1) ◽  
pp. 273-281 ◽  
Author(s):  
Charles S. White ◽  
Thomas Flukinger ◽  
Jean Jeudy ◽  
Joseph J. Chen
Keyword(s):  
Lung Cancer ◽  
Chest Radiography ◽  
Detection System ◽  
Computer Aided Detection ◽  
Computer Aided

scholarly journals Computer-aided detection system for lung cancer in computed tomography scans: Review and future prospects

2014 ◽  
Vol 13 (1) ◽  
pp. 41 ◽  
Author(s):  
Macedo Firmino ◽  
Antônio H Morais ◽  
Roberto M Mendoça ◽  
Marcel R Dantas ◽  
Helio R Hekis ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Detection System ◽  
Computer Aided Detection ◽  
Future Prospects ◽  
Computed Tomography Scans ◽  
Computer Aided

Development of a computer-aided detection system for lung cancer diagnosis

1992 ◽  
Author(s):  
Hideo Suzuki ◽  
Noriko Inaoka ◽  
Hirotsugu Takabatake ◽  
Masaki Mori ◽  
Soichi Sasaoka ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Diagnosis ◽  
Detection System ◽  
Computer Aided Detection ◽  
Lung Cancer Diagnosis ◽  
Computer Aided

Clinical test results of computer-aided detection system for lung cancer using helical CT images

2001 ◽  
Author(s):  
Kazuhori Kubota ◽  
Mitsuru Kubo ◽  
Yoshiki Kawata ◽  
Noboru Niki ◽  
Kenji Eguchi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Detection System ◽  
Helical Ct ◽  
Ct Images ◽  
Clinical Test ◽  
Test Results ◽  
Computer Aided Detection ◽  
Computer Aided

Computer Aided Detection system for the Classification of Non Small Cell Lung Lesions using SVM

2020 ◽  
Vol 16 ◽  
Author(s):  
Shruti Jain
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Detection System ◽  
Small Cell ◽  
Svm Classifier ◽  
Computer Aided Detection ◽  
Small Cell Lung ◽  
Computer Aided

: Lung carcinoma is most commonly occurring death through cancer across the world that mainly occurs due to Smoking. Small cell lung cancer and Non small cell lung cancer (NSCLC) are the two different types of Lung cancer. For the detection and classification of lung cancer, there are different techniques in the literature. This paper emphasis on the three class classification of the Adenocarcinomas, Squamous cell carcinomas, and large cell carcinomas of NSCLC . For precise and superior results, Computer Aided Detection (CADe) system is designed so that the radiologist can diagnose the carcinoma in the ultrasonic images comfortably. CADe analyses the quality of the images, select region of interest, preprocess the data, extract the features and classify the cancer. After exhaustive literature survey, Laws’ mask and SVM classifier with Gaussian RBF kernels is used in this paper. The experimentations were performed on 92 images using 50% - 50% training and testing criteria. The comparative study reveals that our system for separating three class lung cancer provides 95.65% average accuracy for Laws' mask 3 dimensions using SVM classifier that is maximum among the existing methods reported in the literature using the same dataset.

Accuracy of Segmentation of a Commercial Computer-aided Detection System for Mammography

Radiology ◽  
2005 ◽  
Vol 235 (2) ◽  
pp. 385-390 ◽  
Author(s):  
Jay A. Baker ◽  
Eric L. Rosen ◽  
Michele M. Crockett ◽  
Joseph Y. Lo
Keyword(s):  
Detection System ◽  
Computer Aided Detection ◽  
Computer Aided
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