Open Access
| Issue |
MATEC Web of Conferences
Volume 57, 2016
4th International Conference on Advancements in Engineering & Technology (ICAET-2016)
|
|
|---|---|---|
| Article Number | 02011 | |
| Number of page(s) | 6 | |
| Section | Information Systems & Computer Science Engineering | |
| DOI | https://doi.org/10.1051/matecconf/20165702011 | |
| Published online | 11 May 2016 | |
- T. Rajesh, R. Suja Mani Malar, (2013) “Rough Set Theory and Feed Forward Neural”, international conference on advance nanomaterials and emerging engineering technologies (ICANMEET), pp 240-244.. [Google Scholar]
- Atiq Islam, Syed M. S. Reza, and Khan M. Iftekharuddin,(2013) “Multifractal Texture Estimation for Detection and Segmentation of Brain Tumors” IEEE Transactions On Biomedical Engineering, Vol. 60, No. 11, pp 3204-3215. [CrossRef] [Google Scholar]
- Eyup Emre Ulku, Ali Yilmaz Camurcu, (2013) “Computer Aided Brain Tumor Detection With Histogram Equalization And Morphological Image Processing Techniques”, ICECCO, pp 48-51. [Google Scholar]
- P Dvorak, W Kropatsch, and K Bartusek ,(2013) “Automatic Detection of Brain Tumors in MR Images”, Telecommunication and Signal Processing, pp 577-5802. [Google Scholar]
- J. Vijay, J. Subhashini,(2013) “An Efficient Brain Tumor Detection Methodology using k-means clustering algorithm” International conference on Communication and Signal Processing, pp 653-657. [Google Scholar]
- I Maiti , Dr. Monisha Chakraborty, (2012) ,“A New Method for Brain Tumor Segmentation Based on Watershed and Edge Detection Algorithms in HSV Colour Model”, Computing and communication systems (NCCCS), pp 1-5. [Google Scholar]
- Natarajan P, Krishnan.N, Natasha Sandeep Kenkre, Shraiya Nancy, Bhuvanesh Pratap Singh, “Tumor Detection using threshold operation in MRI Brain Images”, Computational intelligence and computing research (ICCIC) IEEE International conference, pp 1-4. [Google Scholar]
- Azian Azamimi Abdullah, Bu Sze Chize,(2012) Yoshifumi Nishio, “Implementation of An Improved Cellular Neural Network Algorithm For Brain Tumor Detection”, International Conference on Biomedical Engineering (ICOBE), pp 611-615. [Google Scholar]
- China, Phooi Yee Lau, Frank C. T. Voon, and Shinji Ozawa, (2009)“The detection and visualization of brain tumors on T2-weighted MRI images using multiparameter feature blocks”, Engineering in Medicine and Biology 27th Annual Conference, pp 5104-5107. [Google Scholar]
- P. Singh, (2013) “A new approach to image segmentation”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, No. 4.. [Google Scholar]
- H. G. Kaganami and Z. Beij,(2009) “Region based detection versus edge detection,” IEEE Transactions on Intelligent Information Hiding and Multimedia Signal Processing, pp. 1217-1221. [Google Scholar]
- X. iang, R. Zhang, and S. Nie,(2009) “Image segmentation based on PDEs model: A survey”, in Proc. 3rd International Conference on Bioinformatics and Biomedical Engineering, pp. 1-4. [Google Scholar]
- B. C. Wei, R. Mandava, (2010) “Multiobjective optimization Approaches in Image Segmentation- the Direction and Challenges”, ICSRS Publication. [Google Scholar]
- W.D. Heiss, P. Raab, and H. Lanfermann, (2011)“Multimodality assessment of brain tumors and tumor recurrence,” J. Nucl. Med., Vol. 52, No. 10, pp. 1585–1600. [CrossRef] [Google Scholar]
- Dongjin Kwon, (2014) “PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration” ieee transactions on medical imaging”, Vol. 33, No. 3, pp. 0278-0062. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.