Abstract
Computer aided detection system was developed to identify the pulmonary nodules to diagnose the cancer cells. Main aim of this research enables an automated image analysis and malignancy calculation through data and CPU infrastructure. Our proposed algorithm has improvement filter to enhance the imported images and for nodule selection and neural classifier for false reduction. The proposed model is experimented in both internal and external nodules and the obtained results are shown as response characteristics curves.
References
Lee,S,L,A., Kouzani,A,Z., Hu,E, J.: Automated Detection of Lung Nodules in Computed Tomography Images: a review. In: Machine Vision and Applications. vol. 23, pp. 151-163. Springer (2012)
Ezhil E, Nithila.,S.S. Kumar,S, S.: Segmentation of Lung Nodule in CT Data using Active Contour Model and Fuzzy C-mean Clustering. In: Alexandria Engineering Journal. vol. 55, pp. 2583-2588. Elsevier(2016)
Nascimento, L,B., De Paiva, A, C., Silva, A, C.: Lung nodules classification in CT images using Shannon and Simpson diversity indices and SVM. In: Machine Learning and Data Mining in Pattern Recognition. pp. 454-466. (2012)
Mehdi Aliloub.,Vassili Kovalev., Eduard Snezhko.,Vahid Taimouri .:A Comprehensive Framework for Automatic Detectıon of Pulmonary Nodules in Lung CT Images. In: Image Anal Stereol. vol. 33, pp. 13-27. (2014)
Wook-Jin Choi.,Tae-Sun Choi .: Automated Pulmonary Nodule Detection System in Computed Tomography Images: A Hierarchical Block Classification Approach. In: Entropy. vol. 15, pp. 507-523. (2013)
Ezhil E, Nithila.,S.S. Kumar,S, S.: Automatic detection of solitary pulmonary nodules using swarm intelligence optimized neural networks on CT images. In: Engineering Science and Technology. vol. 20, pp. 1192–1202. (2017)
Mehrdad Moghbel.,Syamsiah Mashohor.,Rozi Mahmud.,Iqbal Bin Saripan. M. :Automatic Liver Tumor Segmentation on Computed Tomography for Patient Treatment Planning and Monitoring. In: EXCLI Journal. vol.15, pp. 406-423. (2016)
Alex Martins Santos., Antonio Oseasde Carvalho Filho., Aristofanes Correa Silva., Anselmo Cardoso de Paiva ., Rodolfo Acatauassu Nunes., Marcelo Gattass. : Automatic Detection of Small Lung Nodules in 3DCT Data using Gaussian Mixture Models, Tsallis Entropy and SVM. In: Engineering Applications of Artificial Intelligence. vol.36, pp. 27–39. Elsevier (2014)
Juan juan Zhao., Guo hua Ji.: Cavitary Nodule Segmentation in Computed Tomography Images Based on Self-Generating Neural Networks and Particle Swarm Optimisation. Int. J. Bio-Inspired Computation. vol. 7, pp. 62-67. (2015)
Gonc alves ,L., Novo,J., Cunha,A., Campilho .: Evaluation of the Degree of Malignancy of Lung Nodules in Computed Tomography Images. In: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), pp. 74-80. (2017)
Pablo G, Cavalcanti., Shahram Shirani., Jacob Scharcanski., Crystal Fong., Jane Meng., Jane Castelli., David Koff .: Lung Nodule Segmentation in Chest Computed Tomography using a Novel Background Estimation Method. In: Quant Imaging Med Surg. Vol.6, pp. 16-24. (2016)
Temesguen Messay., Russell C, Hardie ., Timothy R, Tuinstra .: Segmentation Of Pulmonary Nodules In Computed Tomography using a Regression Neural Network Approach and Its Application to the Lung Image Database Consortium and Image Database Resource Initiative Dataset. In: Medical Image Analysis. vol.22, pp. 48–62. Elsevier (2015)
Amal A,Farag., James H,Graham .:A Novel Approach for Lung Nodules Segmentation in Chest CT Using Level Sets. In: IEEE Transactıons on Image Processing, vol. 22, pp. 5202-5213. (2013)
Qiu Shi.,Wendesheng.,Cui Ying.,Feng Jun .: Lung Nodules Detection in CT Images Using Gestalt-Based Algorithm. In: Chinese Journal of Electronics vol.25, pp.711-718. (2016)
Stefano Diciotti., Simone Lombardo., Massimo Falchini., Giulia Picozzi., Mario Mascalch .: Automated Segmentation Refinement of Small Lung Nodules in CT Scans by Local Shape Analysis. In: IEEE Transactions on Biomedical Engineering, vol. 58, pp.3418-3428. (2011)
Shaik Parveen,S., Kavitha, C .: Segmentation of CT Lung Nodules using FCM with Firefly Search Algorithm. In: IEEE 2nd International Conference on Innovations in Information Embedded and Communication Systems ICIIECS'15. (2015)
Hang Zhang., Xi Wang., Parisa Memarmoshrefi.,Dieter Hogrefe .: A Survey of Ant Colony Optimization Based Routing Protocols for Mobile Ad Hoc Networks. In: IEEE Access. vol.5, pp. 24139-24161. (2017)
Meng Ma.,Chuang Sun.,Xuefeng Chen .: Discriminative Deep Belief Networks with Ant Colony Optimization for Health Status Assessment of Machine. In:IEEE Transactions on Instrumentation and Measurement, vol.66, pp.3115-3125.(2017)
Feifei Zheng., Aaron C, Zecchin., Jeffery P, Newman., Holger R,Maier., Graeme C, Dandy .: An Adaptive Convergence-Trajectory Controlled Ant Colony Optimization Algorithm with Application to Water Distribution System Design Problems. In: IEEE Transactions on Evolutionary Computation. vol.21, pp.773 -791.(2017)
Michalis Mavrovouniotis., Felipe M, Müller., Shengxiang Yang .: Ant Colony Optimization with Local Search for Dynamic Traveling Salesman Problems. In:IEEE Transactions on Cybernetics. vol.47, pp. 1743-1756. (2017)
Yongjun Sun., Wenxin Dong., Yahuan Chen .: An Improved Routing Algorithm Based on Ant Colony Optimization in Wireless Sensor Networks. In: IEEE Communications Letters. vol.21, pp. 1317 - 1320. (2017)
Shun-Hung Tsai., Yu-Wen Chen .: A Novel Fuzzy Identification Method Based on Ant Colony Optimization Algorithm. In: IEEE Access. vol.4, pp. 3747 - 3756. (2016)
Xu Huang., Raul Fernandez-Rojas., Keng-Liang Ou .: Signal Processing of Brain Activity with Ant Colony Optimization and Wavelet Analysis using Near Infrared Spectroscopy. In: IEEE Sixth International Conference on Communications and Electronics. Pp. 306 - 311. (2016)