JOURNAL ARTICLE

Computerized brain tumor segmentation in magnetic resonance imaging

Maryana de Carvalho AlegroEdson AmaroRosei de Deus Lopes

Year: 2012 Journal:   Einstein (São Paulo) Vol: 10 (2)Pages: 158-163   Publisher: Instituto Israelita de Ensino e Pesquisa Albert Einstein

Abstract

OBJECTIVE: To propose an automatic brain tumor segmentation system. METHODS: The system used texture characteristics as its main source of information for segmentation. RESULTS: The mean correct match was 94% of correspondence between the segmented areas and ground truth. CONCLUSION: Final results showed that the proposed system was able to find and delimit tumor areas without requiring any user interaction.

Keywords:
Segmentation Magnetic resonance imaging Artificial intelligence Ground truth Brain tumor Computer vision Computer science Texture (cosmology) Image segmentation Pattern recognition (psychology) Image (mathematics) Medicine Radiology Pathology

Metrics

10
Cited By
0.55
FWCI (Field Weighted Citation Impact)
29
Refs
0.67
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Brain Tumor Detection and Classification
Life Sciences →  Neuroscience →  Neurology
AI in cancer detection
Physical Sciences →  Computer Science →  Artificial Intelligence
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