3D Fetal Face Reconstruction from Ultrasound Imaging

Alomar, Antònia; Morales, Araceli; Vellvé, Kilian; Porras, Antonio R.; Crispi, F.; Linguraru, Marius George; Piella, Gemma; Sukno, Federico M.

doi:10.5220/0010340306150624

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…In particular, morphable face models have been used to describe facial dysmorphisms 19,20 with potential applications such as the early detection of genetic syndromes 21 . The quantitative analysis of the fetal face has however been limited by the difficult reconstruction of the 3D surface 17 .…”

Section: Shape Referencementioning

confidence: 99%

Fetal face shape analysis from prenatal 3D ultrasound images

Sivera,

Clark,

Dall’Asta

et al. 2024

Sci Rep

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Abstract3D ultrasound imaging of fetal faces has been predominantly confined to qualitative assessment. Many genetic conditions evade diagnosis and identification could assist with parental counselling, pregnancy management and neonatal care planning. We describe a methodology to build a shape model of the third trimester fetal face from 3D ultrasound and show how it can objectively describe morphological features and gestational-age related changes of normal fetal faces. 135 fetal face 3D ultrasound volumes (117 appropriately grown, 18 growth-restricted) of 24-34 weeks gestation were included. A 3D surface model of each face was obtained using a semi-automatic segmentation workflow. Size normalisation and rescaling was performed using a growth model giving the average size at every gestation. The model demonstrated a similar growth rate to standard head circumference reference charts. A landmark-free morphometry model was estimated to characterize shape differences using non-linear deformations of an idealized template face. Advancing gestation is associated with widening/fullness of the cheeks, contraction of the chin and deepening of the eyes. Fetal growth restriction is associated with a smaller average facial size but no morphological differences. This model may eventually be used as a reference to assist in the prenatal diagnosis of congenital anomalies with characteristic facial dysmorphisms.

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Section: Shape Referencementioning

confidence: 99%

Fetal face shape analysis from prenatal 3D ultrasound images

Sivera,

Clark,

Dall’Asta

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Similarly, deep learning approaches have been proposed 15,16 but the task difficulty and the limited existing ground-truth data that could be leveraged to build and validate a new model limit the quality of the results, and the reconstructions are often rough or incomplete. The method proposed by Alomar et al 17 demonstrates promising results, is based on a model developed for the faces of newborn babies and requires the manual placement of a large number of landmarks. The reconstructions therefore approximate more closely to a newborn rather than fetal fetal face shape, particularly for earlier gestational ages.…”

Section: Introductionmentioning

confidence: 99%

Fetal face shape analysis from prenatal 3D ultrasound images

Sivera

Clark

Dall’Asta

et al. 2023

Preprint

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3D ultrasound imaging of fetal faces has been predominantly confined to qualitative assessment. Many genetic conditions evade diagnosis and identification could assist with parental counselling, pregnancy management and neonatal care planning. We describe a methodology to build a shape model of the third trimester fetal face from 3D ultrasound and show how it can objectively describe morphological features and gestational-age related changes of normal fetal faces. 135 fetal face 3D ultrasound volumes (117 appropriately grown, 18 growth-restricted) of 24-34 weeks gestation were included. A 3D surface model of each face was obtained using a semi-automatic segmentation workflow. Size normalisation and rescaling was performed using a growth model giving the average size at every gestation. The model demonstrated a similar growth rate to standard head circumference reference charts. A landmark-free morphometry model was estimated to characterize shape differences using non-linear deformations of an idealized template face. Advancing gestation is associated with widening/fullness of the cheeks, contraction of the chin and deepening of the eyes. Fetal growth restriction is associated with a smaller average facial size but no morphological differences. This model may eventually be used as a reference to assist in the diagnosis of congenital anomalies with characteristic facial dysmorphisms.

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“…Three-dimensional (3D) face reconstruction from uncalibrated two-dimensional (2D) images is a long-standing problem in computer vision with many different applications, such as face recognition [1,2,3,4], face alignment [5,6,7,8], image edition [9,10,11], face animation [12,13,14], age estimation [15], or medical diagnostic purposes [16,17,18]. Despite its great amount of advantages, 3D face reconstruction is a very challenging task since it is inherently ill-posed.…”

Section: Introductionmentioning

confidence: 99%

BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs

Morales¹,

Porras²,

Linguraru³

et al. 2022

Preprint

Self Cite

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We present a 3D face reconstruction system that aims at recovering the 3D facial geometry of babies from uncalibrated photographs, BabyNet. Since the 3D facial geometry of babies differs substantially from that of adults, baby-specific facial reconstruction systems are needed. BabyNet consists of two stages: 1) a 3D graph convolutional autoencoder learns a latent space of the baby 3D facial shape; and 2) a 2D encoder that maps photographs to the 3D latent space based on representative features extracted using transfer learning. In this way, using the pre-trained 3D decoder, we can recover a 3D face from 2D images. We evaluate BabyNet and show that 1) methods based on adult datasets cannot model the 3D facial geometry of babies, which proves the need for a babyspecific method, and 2) BabyNet outperforms classical model-fitting methods even when a baby-specific 3D morphable model, such as BabyFM, is used.

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3D Fetal Face Reconstruction from Ultrasound Imaging

Cited by 4 publications

References 12 publications

Fetal face shape analysis from prenatal 3D ultrasound images

Fetal face shape analysis from prenatal 3D ultrasound images

Fetal face shape analysis from prenatal 3D ultrasound images

BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs

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