CT scan image segmentation based on hounsfield unit values using Otsu thresholding method

Research output: Contribution to journalConference articlepeer-review

15 Citations (Scopus)

Abstract

The use of medical images in diagnosing and analyzing various cases in the medical field is commonly used. In certain cases, the image used is not limited to two-dimensional images, but sometimes requires the use of three-dimensional images. CT scan image is an image that has several image slices that can be reconstructed into a three-dimensional image. In the reconstruction process, segmentation plays an important role to get a good reconstruction result and reduce the resulting noise. This study aims to develop a method used in CT scan image segmentation, with the hope that it can simplify the diagnosis process performed by doctors using two-dimensional images or those that have been constructed into three-dimensional images. The main method developed is the Otsu Thresholding method based on the threshold value, which is combined with the Hounsfield unit (HU) value which will be the input for the segmentation process. The image used is a thorax CT scan image with the final goal to get the results of heart segmentation. The results obtained based on the calculation of balanced accuracy for the 30 data tested had an average of 72.54%. The highest result of balanced accuracy for heart segmentation was obtained by data 4 of 77.43%, while the lowest result was obtained by data 29 of 69.1%.

Original languageEnglish
Article number012080
JournalJournal of Physics: Conference Series
Volume1816
Issue number1
DOIs
Publication statusPublished - 8 Mar 2021
Event10th International Conference on Theoretical and Applied Physics, ICTAP 2020 - Mataram, West Nusa Tenggara, Indonesia
Duration: 20 Nov 202022 Nov 2020

Fingerprint

Dive into the research topics of 'CT scan image segmentation based on hounsfield unit values using Otsu thresholding method'. Together they form a unique fingerprint.

Cite this