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
کلیدواژهها
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
شیوه ارجاع
Aminian Dehkordi, Mahsa and Ayat, Saeed,1395,Brain Tumor Image processing: A glance to recent studies, International Conference on Engineering and Computer Science,Najafabad
ارائهشده در
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