A Deep Learning Approach Combining CNN and LSTM for classifying Magnetic Resonance Brain tumor
Publish place: 13th International Conference on Information Technology, Computers and Telecommunications
Publish Year: 1400
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ITCT13_047
تاریخ نمایه سازی: 10 آذر 1400
Abstract:
One of the main challenges in treating tumors and assessing disease progression is diagnosing tumor size And distinguish tumor types from each other. Manual tumor segmentation in three-dimensional Magnetic Resonance images (volume MRI) is a time-consuming and tedious task. Its accuracy depends heavily on the operator's experience doing it. The need for an accurate and fully automatic method for segmenting brain tumors and measuring tumor size is strongly felt. This paper first uses a combined CNN-LSTM method to detect HG and LG tumors in ۳D brain images. Then it used the UNET Neural Network to improve the location of the tumor in the brain. In this article, we use BRATS ۲۰۱۸ database images, And manual segmentation is used as the Grand truth. in this paper, we showed that the proposed method could effectively perform segmentation.
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Authors
Asieh Emrani
Master of Computer Engineering, ImamReza International University, Mashhad, Iran
Mahla Zibaei
Bachelor of Computer Engineering, Islamic Azad university of Mashhad, Mashhad, Iran
Shiva Sanati
PhD Student in Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran