Proposed A Deep Learning Approach for Brain tumor Segmentation
Publish place: Sixth International Conference on Information Technology Computer and Telecommunication Engineering Iran
Publish Year: 1401
نوع سند: مقاله کنفرانسی
زبان: English
View: 213
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICTBC06_041
تاریخ نمایه سازی: 1 اسفند 1401
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.
Keywords:
Authors
Neda Nosrati
Master of Computer Engineering, Islamic Azad university of Mashhad, Mashhad, Iran
Shirin Sanati
Master of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, Iran