Hapsari Peni Agustin and Hanik Badriyah Hidayati and Adri Gabriel Sooai and I Ketut Eddy Purnama and Mauridhi Hery Purnomo (2019) Volumetric Analysis of Brain Tumor Magnetic Resonance Image. In: 2019 International Conference of Computer Engineering, Network, and Intelligent Multimedia (CENIM). IEEE, Surabaya, pp. 1-6. ISBN 978-1-7281-2965-5

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Abstract

Volumetric analysis of brain tumors is a decisive thing in the detection of brain tumors to determine the patient's lifetime followed by action to the patient. A few studies had been shown explicitly quantified the brain tumor volume while the analysis of brain tumor volumetric by expert limited with the huge data of brain tumor patient MRI. Thorough the importance of brain tumor analysis in clinical used, the purpose of this research is to evaluate the similarity of a semi-automatic segmentation tool for brain tumor image analysis. The agreement was compared by using differences of means with 95% limits of agreement (LoA). Brain tumor segmentation was obtained by using Fast Marching and Grow Cut segmentation methods. Preoperative MRI images of 20 T2 MRI of low-grade glioma patients from The Cancer Imaging Archive (TCIA) database were used to analyze brain tumor volume. The volume obtained from the two segmentation methods is based on the similarity between the two using the intra-method agreement between two segmentation methods with a 95% limit of agreement (LoA) value and difference volume average of 920 mm 3 or 0.92 mL. Its shown that both methods had the same performance.

Item Type:	Book Section
Uncontrolled Keywords:	Fast Marching, Grow Cut, Limits of Agreement, Difference of Volume Average
Subjects:	R Medicine > R Medicine (General) R Medicine > RC Internal medicine
Divisions:	01. Fakultas Kedokteran > Ilmu Penyakit Saraf
Creators:	Creators NIM Hapsari Peni Agustin UNSPECIFIED Hanik Badriyah Hidayati NIDN0024097808 Adri Gabriel Sooai UNSPECIFIED I Ketut Eddy Purnama UNSPECIFIED Mauridhi Hery Purnomo UNSPECIFIED
Depositing User:	arys fk
Date Deposited:	09 Apr 2021 03:24
Last Modified:	09 Apr 2021 03:24
URI:	http://repository.unair.ac.id/id/eprint/105310
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