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Proceedings Paper

Fetal biometric measurements during the first trimester of pregnancy
Author(s): María Georgina Bracamontes Piña; Erik Bojorges-Valdez; Lisbeth Camargo Marín; Mario Guzmán Huerta; Moisés Sánchez Rivera; Verónica Medina Bañuelos
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Paper Abstract

During the first trimester of pregnancy fetal health assessment is especially important. In the clinical practice, the gestational sac (GS) volume estimation is manually done using a tedious procedure which is prone to physicians' subjectivity. The method proposed in this paper consists on a semiautomatic delimitation of the GS and a segmentation of its content with minimal expert intervention. It is based on spreading active contours (SAC), following a planimetric strategy to define the GS' edges. Additionally, an optimal thresholding method was used to separate solid matter and amniotic fluid. The comparison between manual GS segmentations and those obtained with the proposed SAC method, shows Dice similarities of 90% and a mean Hausdor distance of 5.63 ± 1.94 mm, while the correlation index between SAC and the clinical reference (VOCAL) is 0.997. However, with statistical tests (t-paired) a value of p < 0.05 was obtained, which suggests a difference in the measured volume by the compared methods. The proposed method (SAC) has shown to be reliable, besides of being easy to implement.

Paper Details

Date Published: 26 January 2017
PDF: 6 pages
Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 1016006 (26 January 2017); doi: 10.1117/12.2256899
Show Author Affiliations
María Georgina Bracamontes Piña, Univ. Iberoamericana (Mexico)
Erik Bojorges-Valdez, Univ. Autónoma Metropolitana (Mexico)
Lisbeth Camargo Marín, Instituto Nacional de Perinatología (Mexico)
Mario Guzmán Huerta, Instituto Nacional de Perinatología (Mexico)
Moisés Sánchez Rivera, Univ. Autónoma Metropolitana (Mexico)
Verónica Medina Bañuelos, Univ. Autónoma Metropolitana (Mexico)

Published in SPIE Proceedings Vol. 10160:
12th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Jorge Brieva; Ignacio Larrabide; , Editor(s)

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