Details

Autor(en) / Beteiligte

• Shahariar Ayon, Ragib
• Robaiat Mou, Jannatul
• Hossain Majed, Sharafat
• Rifat, Rathyatul

Titel

Brain Tumor Segmentation and Classification using Spatial Fuzzy C mean and Quadratic Support Vector Machine

Ist Teil von

• 2019 3rd International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), 2019, p.233-236

Ort / Verlag

IEEE

Erscheinungsjahr

2019

Quelle

IEEE Xplore

Beschreibungen/Notizen

• Precise detection and classification of brain tumors at a reasonable time is vital to enhance the survival of a patient. But due to the big dimensional and anatomical diversity between brain tumors, this is a difficult job. In this contribution, we are proposing an improved spatial fuzzy c-mean (SFCM) for brain tumor segmentation and a quadratic support vector machine (QSVM) for tumor type classification. When applied to the BraTS 2018 dataset, the acquired segmentation outcomes were shown to be 7.16% and 12.78% better than the conventional fuzzy c-mean (FCM) and k-mean. This method assists radiologists in understanding the medical image and gives a second opinion.