Title: Foetal brain extraction using mathematically modelled local foetal minima

Authors: P. Durgadevi; S. Vijayalakshmi

Addresses: School of Computing Science and Engineering, Galgotias University, India; Computer Science and Engineering, Galgotias College of Engineering and Technology, India ' Department of Data Science, Christ University, India

Abstract: This paper proposes segmentation techniques to separate brain parcel from the MRI of the human embryo and also determines the abnormality of the foetal brain at various gestational weeks. These strategies mean to characterise areas of the premium of various granularities: brain, tissue types, or constructions that are more limited. Various philosophies have been applied for this division task and can be grouped into the solo, parametric, characterisation, atlas combination, and deformable models. Brain atlases are usually used as preparing information in the division interaction. Difficulties identifying using pictures secured, the quick mental health, and the restricted accessibility of imaging information thwart this division task. This paper discusses foetal brain segmentation using mathematically modelled foetal brain minima by using a curve fitting segmentation technique. Broad tests show that the proposed approach beats the ebb and flow of various segmentation techniques and the results gained are significant.

Keywords: foetal MRI; brain localisation; foetal minima; automatic curve fitting; smoothing filter; thresholding; segmentation; structural similarity index; SSIM; gestational weeks; GW; magnetic resonance imaging; MRI.

DOI: 10.1504/IJBET.2023.132544

International Journal of Biomedical Engineering and Technology, 2023 Vol.42 No.3, pp.225 - 243

Received: 16 Feb 2021
Accepted: 19 Sep 2021
Published online: 28 Jul 2023 *

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