सूचना प्रौद्योगिकी और सॉफ्टवेयर इंजीनियरिंग जर्नल

सूचना प्रौद्योगिकी और सॉफ्टवेयर इंजीनियरिंग जर्नल
खुला एक्सेस

आईएसएसएन: 2165- 7866

अमूर्त

Detecting Brain Tumour in Early Stage Using Deep Learning

Probuddha Konwar, Julius Bhadra, Manash Jyoti Dutta, Jintu Dowari

In brain tumors treatment planning and quantitative evaluation, determining the tumors extent is a major challenge. Noninvasive Magnetic Resonance Imaging (MRI) has developed as a front-line diagnostic technique for brain malignancies without the use of ionizing radiation. Segmenting the extent of a brain tumor manually from 3D MRI volumes is a time-consuming process that relies greatly on operator competence. For correct tumors extent evaluation, a reliable fully automated brain tumors segmentation approach is required in this scenario. We present a completely automated brain tumors segmentation method based on U-Net deep convolutional networks in this paper. The Multimodal Brain Tumor Image Segmentation (BRATS 2015) datasets were utilized to test our approach, which included 220 high-grade brain tumors.

अस्वीकरण: इस सार का अनुवाद कृत्रिम बुद्धिमत्ता उपकरणों का उपयोग करके किया गया था और अभी तक इसकी समीक्षा या सत्यापन नहीं किया गया है।
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