Fast ellipse fitting implementation on usg mobile telehealth application

Made Wira Dhanar Santika, Muhammad Anwar Masum, Aria Kekalih, Alhadi Bustamam, Adila Alfa Krisnadhi, Noor Akhmad Setiawan, I. Made Agus Dwi Suarjaya, Adi Nurhadiyatna, Wisnu Jatmiko

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Fetal head circumference (HC) is one of the most important biometrics in assessing fetal growth during prenatal ultrasound examinations. However, measuring the fetal head is not an easy task. This study aims to create an automatic fetal head measurement system. This system is expected to run on mobile devices as part of telehealth system. HC measurement can be done with object detection method, followed by edge detection, then using every edge pixel, fetal head can be approximated using ellipse fitting. Evaluations are carried out using hit rates and error rates for ellipse fitting. From each method that was tested, the evaluation result showed that the Adaptive Boosting and Fast Ellipse Fitting (ElliFit) method had the best performance. This method also had a relatively fast execution time for a mobile device, which is 3-5 seconds.

Original languageEnglish
Title of host publication2020 International Workshop on Big Data and Information Security, IWBIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages59-63
Number of pages5
ISBN (Electronic)9781728190983
DOIs
Publication statusPublished - 17 Oct 2020
Event5th International Workshop on Big Data and Information Security, IWBIS 2020 - Depok, Indonesia
Duration: 17 Oct 202018 Oct 2020

Publication series

Name2020 International Workshop on Big Data and Information Security, IWBIS 2020

Conference

Conference5th International Workshop on Big Data and Information Security, IWBIS 2020
Country/TerritoryIndonesia
CityDepok
Period17/10/2018/10/20

Keywords

  • Adaptive Boosting
  • ElliFit
  • Fetal Head Circumference
  • USG

Fingerprint

Dive into the research topics of 'Fast ellipse fitting implementation on usg mobile telehealth application'. Together they form a unique fingerprint.

Cite this