[1]
Armato SG, Giger ML, Moran CJ, Blackburn JT, Doi K, MacMahon H. Computerized detection of pulmonary nodules on CT scans. Radiographics 1999; 19(5): 1303-11.
[2]
Ruprah TS. Face recognition based on pca algorithm. Int J Comput Sci Inform 2012; 2(1): 221-5.
[3]
Ada RajneetK. Early detection and prediction of lung cancer survival using neural network classifier. IJAIEM 2013; 2(6): 375-83.
[4]
Tao Y, Lu L, Dewan M, et al. Multi-level ground glass nodule detection and segmentation in CT lung images. In: Yang GZ, Hawkes D, Rueckert D, Noble A, Taylor C, Eds. International Conference on Medical Image Computing and Computer-Assisted Intervention. September 20-24, 2009; London: UK. 715-23.
[5]
Sharma D, Jindal G. Computer aided diagnosis system for detection of lungcancer in CT scan images. IJECE 2011; 3(5): 714-8.
[6]
Zhao B, Reeves AP, Yankelevitz D, Henschke CI. Three-dimensional multi-criterion automatic segmentation of pulmonary nodules of helical computed tomography images. Opt Eng 1999; 38(8): 1340-8.
[7]
Villa CH, Anselmo AC, Mitragotri S, Muzykantov V. Red blood cells: supercarriers for drugs, biologicals, and nanoparticles and inspiration for advanced delivery systems. Adv Drug Deliv Rev 2016; 106: 88-103.
[8]
Ganeshan B, Abaleke S, Young RC, Chatwin CR, Miles KA. Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging 2010; 10(1): 137-43.
[9]
Gangotrinathaney Kanakkalyani. Lung cancer detection system on CT images-a survey. IJPRET 2015; 3(9): 848-56.
[10]
Dehmeshki J, Amin H, Valdivieso M, Ye X. Segmentation of pulmonary nodules in thoracic CT scans: A region growing approach. IEEE Trans Med Imaging 2008; 27(4): 467-80.
[11]
Al-tarawneh MS. Lung cancer detection using image processing techniques. Leonardo El J Pract Technol 2012; 11(21): 147-58.
[12]
Yoo Y, Shim H, Yun ID, Lee KW, Lee SU. Segmentation of ground glass opacities by asymmetric multi-phase deformable model. In: Reinhardt JM, Pluim JPW, Eds. Medical Imaging: Image Processing 16 March 2006; San Diego, California, United States; pp. 1-8.
[13]
Blechschmidt RA, Werthschutzky R, Lorcher U. Automated CT image evaluation of the lung: A morphology-based concept. IEEE Trans Med Imaging 2001; 20(5): 434-42.
[14]
Bhat G, Biradar VG, Nalini HS. Artificial Neural Network based Cancer Cell Classification (ANN–C3). Comput Eng Intel Syst 2012; 3(2): 116-9.
[15]
Messay T, Hardie RC, Rogers SK. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery. Med Image Anal 2010; 14(3): 390-406.
[16]
Shi Y, Qi F, Xue Z, et al. Segmenting lung fields in serial chest radiographs using both population-based and patient-specific shape statistics. IEEE Trans Med Imaging 2008; 27(4): 481-94.
[17]
Patil SA, Kuchanur MB. Lung cancer classification using image processing. Int J Eng Innov Technol 2012; 2(3): 37-42.
[18]
Wang Q, Song E, Jin R, et al. Segmentation of lung nodules in computed tomography images using dynamic programming and multidirection fusion techniques1. Acad Radiol 2009; 16(6): 678-88.
[19]
Lingayat NS, Tarambale MR. A computer based feature extraction of lung Nodule in chest x-ray image. Int J Biosci Biochem Bioinform 2013; 3(6): 624-9.
[20]
Okada K, Comaniciu D, Krishnan A. Robust anisotropic Gaussian fitting for volumetric characterization of pulmonary nodules in multislice CT. IEEE Trans Med Imaging 2005; 24(3): 409-23.
[21]
Prasad DV. Lung cancer detection using image processing techniques. IJETT 2013; 3(1): 372-8.
[22]
Hashemi A, Pilevar AH, Rafeh R. Mass detection in lung CT images using region growing segmentation and decision making based on fuzzy inference system and artificial neural network. IJIGSP 2013; 5(6): 16-24.
[23]
Kostis WJ, Reeves AP, Yankelevitz DF, Henschke CI. Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images. IEEE Trans Med Imaging 2003; 22(10): 1259-74.
[24]
Laccetti AL, Pruitt SL, Xuan L, Halm EA, Gerber DE. Early cancer does not adversely affect survival in locally advanced lung cancer: A national SEER-medicare analysis. Lung Cancer 2016; 98: 106-13.
[25]
Larkins DB, Harvey W. Introductory computational science using MATLAB and image processing. Procedia Comput Sci 2010; 1(1): 913-9.
[26]
Bhattacharjee A, Richards WG, Staunton J, et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci USA 2001; 98(24): 13790-5.
[27]
Way TW, Chan HP, Goodsitt MM, et al. Effect of CT scanning parameters on volumetric measurements of pulmonary nodules by 3D active contour segmentation: A phantom study. Phys Med Biol 2008; 53(5): 1295.
[28]
Zinoveva O, Zinovev D, Siena SA, Raicu DS, Furst J, Armato SG. A texture-based probabilistic approach for lung nodule segmentation. In: Kamel M, Campilho A, Eds. International Conference Image Analysis and Recognition. June 22-24, 2011; Springer, Berlin: Heidelberg 21-30.
[29]
Sowmiya T, Gopi M, New BM, Thomas RL. Optimization of lung cancer using modern data mining techniques. Int J Engine Res 2014; 3(5): 309-14.
[30]
Diciotti S, Lombardo S, Coppini G, Grassi L, Falchini M, Mascalchi M. The $LoG $ characteristic scale: A consistent measurement of lung nodule size in CT imaging. IEEE Trans Med Imaging 2010; 29(2): 397-409.
39
3
1
1