Perbandingan Pegukuran Volume Tumor Brain MRI Menggunakan Teknik Manual Dan Metode Active Contour

Maizza Nadia Putri, Irwan Katili, Ahmad Hariri, Tri Asih Budiarti, Gatot Murti Wibowo


Background: A brain tumor is a mass of brain cells that grow abnormally. In radiological terms, a brain tumor is called a space occupying lesion (SOL) which generally means a lump. Radiologists or radiology specialists in identifying brain tumors will analyze the results of Magnetic Resonance Imaging (MRI) Brain images with post-processing techniques using a menu in a 3D editor called the region growing technique.

Methods:This type of research is a quasi-experimental research design using Posttest Only Without Control Group Design. The research plan will be carried out at Hermina Hospital Bekasi using 32 samples of brain tumor MRI images, the sample size is obtained by the sample size formula for two paired populations according to Sastroasmoro (2011). Bivariate data analysis, if the data is normally distributed (p value > 0.05), then the Paired T-test statistical test is performed and if the data is not normally distributed (p value <0.05) the Wilcoxon statistical test is performed.

Results: The results of the analysis of brain tumors are followed by manual measurement of tumor volume using the region growing technique. It requires sufficient expertise and experience so that the diagnosis of tumor volume is given precisely and accurately so that its handling can be carried out wisely Evaluation of MRI images requires high accuracy, but doctors can make mistakes because the diagnosis is still done manually, such as errors in diagnosing the location of the tumor and the size of the object. The very complex structure of the human brain also presents its own difficulties in identifying brain tumors. Subjective factors can also affect manual doctor evaluations such as fatigue and uncontrolled time in evaluating an MRI image so that a digital image processing program is needed that can be done with a computational machine to assist doctors in evaluating an MRI image automatically. The active contour method can solve the problem of topological changes in a brain tumor image.

Conclusion: The active contour method is able to classify images with high accuracy. So that it can increase the accuracy of the segmentation process for easy and fast medical diagnosis. The calculation of the volume of brain tumors can be done using the binaryization method which has been segmented through the final image produced by the active contour method. Tumor segmentation and automatic tumor volume calculation have great potential in clinical treatment by freeing doctors from the burden of manual labeling, digital image processing of brain tumors using the active contour method can be used as a complement to the MRI modality that radiologists can use in calculating brain tumor mass volume calculations


tumor calculation volume; active contour methode; region growing; digital image processing

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