ANFIS Based Tumor Detection in Thoracic Images
Author Affiliations
- 1Embedded Systems, Karunya University, Coimbatore, Tamilnadu, INDIA
Res. J. Recent Sci., Volume 3, Issue (ISC-2013), Pages 45-49, (2014)
Abstract
Lung is an important organ in our body which performs its function in both respiratory system and circulatory system. For lung cancer staging, a regional lymph node is important, and an automated system is used to detect both types of abnormalities. A fully automatic differentiation method for Lung tumor and diseased lymph node from CT image of thoracic region is used to calculate the false positive. The performance of detection and differentiation done in three stages, initially detect all potential abnormalities in thoracic image, the lung tumor and diseased lymph nodes are differentiated. Finally Benign and Malignant tumors are classified. Fuzzy logic and Neural Network in MATLAB are used to perform the tasks and also to reduce false positive rate.
References
- Yang Song, Weidong Cai, Jinman Kim and David Dagan Feng, Multistage Discriminative Model for Tumor andLymph Node Detection in Thoracic Images, (2011)
- W. De Wever, S. Stroobants, J. Coolen and J.A. Verschakelen, Integrated PET/CT in the staging of nonsmall cell lung cancer:technical aspects and clinical integration, (2009)
- W. Wever, S. Stroobants, J. Coolen, and J. Verschakelen, Integrated PET/CT in the staging of nonsmall cell lung cancer: Technical aspects and clinical integration,Eur. Respir. J., 3, (2009)
- Poonam Bhayan, Gagandeep Jindal, A Segmented Morphological Approach to Detect Tumor in Lung Images, (2011)
- Yuri Boykov, and Vladimir Kolmogorov, An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision, (2004)
- Jan-Martin Kuhnigk, Volker Dicken, Lars Bornemann, Annemarie Bakai, Dag Wormanns, Stefan Krass, and Heinz-Otto Peitgen, Morphological Segmentation and Partial Volume Analysis for Volumetry of Solid Pulmonary Lesions in Thoracic CT Scans, (2006)
- Zhi-Hua Zhou, Yuan Jiang, Yu-Bin Yang, Shi-Fu Chen,Lung Cancer Cell Identification Based on Artificial Neural Network Ensembles, (2002)
- Li Zhang, Weida Zhou, and Licheng Jiao, Wavelet SupportVector Machine, (2004)
- Survey Paper on Diagnosis of Breast Cancer Using Image Processing Techniques, Mussarat Yasmin, Muhammad Sharif and Sajjad Mohsin, Res. J. Recent Sci.,2(10), 88-98 (2013)
- Framework for the Comparison of Classifiers for Medical Image Segmentation with Transform and Moment based features, Maria Hameed, Muhammad Sharif, Mudassar Raza, Syed Waqas Haider, Muhammad Iqbal, Res. J. Recent Sci., 2(6), 1-10 (2013)
- Bone Mineral Density Correlation against Bone Radiograph Texture Analysis: An Alternative Approach, Abdul Basit Shaikh, Muhammad Sarim, Sheikh Kashif Raffat, Mansoor Khan2 and Amin Chinoy, Res. J. Recent Sci.,2(3), 87-91 (2013)
- Anticancer activity of Ethanol extract of Polygala javana DC whole Plant Against Dalton Ascites Lymphoma, Alagammal M., Paulpriya K. and Mohan V.R., Res. J. Recent Sci., 2(2), 18-22 (2013)
- Cherry Ballangan, Xiuying Wang, Michael Fulham, Stefan Eberl, Yong Yin, and Dagan Feng, Automated Delineation of Lung Tumors in PET Images Based on Monotonicity and a Tumor-Customized Criterion, (2011)
- Manaswini Padhan, An Extensive Survey on ArtificialNeural Network Based Cancer Prediction Using Soft-Computing Approach (2011)45-49 (2014)
- Hanford J. Deglint, Rangaraj M. Rangayyan, Fábio J.Ayres, Graham S. Boag, Marcelo K.Zuffo, Three-Dimensional Segmentation of the Tumor in Computed Tomographic Images of Neuroblastoma (2007)
- Y. Song, W. Cai, S. Eberl, M. Fulham, and D. Feng, Discriminative pathological context detection in thoracic imagesbased on multi-level inference, 6893 (2011)
- HBVO: Human Biological Viruses Ontology, Sheikh Kashif Raffat, Mohd. Shahab Siddiqui, Mohd. Siddiq,Zubair A. Shaikh and Abdul Rahman Memon, Res. J. Recent Sci.,1(10), 45-50 (2012)
- OncmiRs: Small Noncoding RNA with Multifaceted Rolein Cancer Joseph Baby and Nair Vrundha M., Res. J. Recent Sci., 1(11), 70-76 (2012)
