Automatic Detection Algorithm of Radiation Surgery Area using Morphological Operation and Average of Brain Tumor Size
Year: 2015
Type: article
Abstract: In this paper, we proposed automatic extraction of brain tumor using morphological operation and statistical tumors size in MR images. Neurosurgery have used gamma-knife therapy by MR images. However, the gamma-knife plan systems needs the brain tumor regions, because gamma-ray should intensively radiate to the brain tumor except for normal cells. Therefore, gamma-knife plan systems spend too much time on designating the tumor regions. In order to reduce the time of designation of tumors, we progress the automatical extraction of tumors using proposed method. The proposed method consist of two steps. First, the information of skull at MRI slices remove using statistical tumors size. Second, the ROI is extracted by tumor feature and average of tumors size. The detection of tumor is progressed using proposed and threshold method. Moreover, in order to compare the effeminacy of proposed method, we compared snap-shot and results of proposed method.
Institution: Kyungpook National University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Award: G4386491937
OpenAlex ID: W2333257516