Brain Tumor Image processing: A glance to recent studies
محل انتشار: کنفرانس بین المللی مهندسی و علوم کامپیوتر
سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 572
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شناسه ملی سند علمی:
ICCSE01_167
تاریخ نمایه سازی: 14 شهریور 1396
چکیده مقاله:
Image processing has been focused in several studies in brain tumor detection from the brain Magnetic Resonance Imaging(MRI) in order to improve accuracy of experts manual inspection. This work is an uptodate concise review of learning machine techniquesin order to analysis their strengths and weaknesses for detection of malignant tissues and improvement of experts diagnostic capability.Many methods were discussed as follows: Threshold-based (Global/Local) , Region-based (Region-growing , Watershed) , Pixel-based(Fuzzy C Means, Markov Random Fields) , Model-based (Parametric Deformable Models, Level Sets ) , The atlas-based segmentation , KNNtechniques , Neural network, K-mean algorithms. Also , hybrid techniques were proposed including Combination of K-means and fuzzyc-means , FKSRG , Multi-region + multi-reference framework ,Generative probabilistic model + spatial regularization , probabilistic modelplus localization , Non-rigid registration / atlas/ MRF , SVM / CRF , Decision Forests / tissue-specific Gaussian mixture models , SVM /Kernel feature selection , etc. We found that the machine learning approaches integrated with other approaches can offer a higher detectionsuccess rate , accuracy and sensitivity rates. But they are time consuming and it is better to improve this matter in the future works.
کلیدواژه ها:
نویسندگان
Mahsa Aminian Dehkordi
Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran
Saeed Ayat
Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad, Iran Department of Computer Engineering, Payame Noor University, Najafabad, Iran