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Development of ground truth data for automatic lumbar spine MRI image segmentation

Natalia, Friska and Meidia, Hira and Afriliana, Nunik and Al-Kafri, Ala S. and Sudirman, Sud and Simpson, Andrew and Sophian, Ali and Al-Jumaily, Mohammed and Al-Rashdan, Wasfi and Bashtawi, Mohammad (2019) Development of ground truth data for automatic lumbar spine MRI image segmentation. In: IEEE 20th International Conference on High Performance Computing and Communications, 16th IEEE International Conference on Smart City and 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018, 28-30 June 2018, Exeter; United Kingdom.

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Artificial Intelligence through supervised machine learning remains an attractive and popular research area in medical image processing. The objective of such research is often tied to the development of an intelligent computer aided diagnostic system whose aim is to assist physicians in their task of diagnosing diseases. The quality of the resulting system depends largely on the availability of good data for the machine learning algorithm to train on. Training data of a supervised learning process needs to include ground truth, i.e., data that have been correctly annotated by experts. Due to the complex nature of most medical images, human error, experience, and perception play a strong role in the quality of the ground truth. In this paper, we present the results of annotating lumbar spine Magnetic Resonance Imaging images for automatic image segmentation and propose confidence and consistency metrics to measure the quality and variability of the resulting ground truth data, respectively.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 7258/72709
Uncontrolled Keywords: Ground truth; Confidence metric; Consistency metric; Lumbar spine MRI; Image segmentation
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: Dr Ali Sophian
Date Deposited: 18 Jun 2019 17:05
Last Modified: 18 Jun 2019 17:05
URI: http://irep.iium.edu.my/id/eprint/72709

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