Low-Cost Smartphone-Based Photogrammetry for the Analysis of Cranial Deformation in Infants

Barbero-García, Inés; Lerma, José Luis; Marqués-Mateu, Ángel; Miranda, Pablo

doi:10.1016/j.wneu.2017.03.015

Cited by 50 publications

(52 citation statements)

References 16 publications

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“…The models were created using a smartphone camera and Agisoft PhotoScan as described by the authors in a previous paper [4].…”

Section: Data Acquisitionmentioning

confidence: 99%

“…Nowadays, the use of 3D models for cranial deformation assessment is becoming more common, but the methodology still needs to be improved [3]. The authors have presented a low-cost, smartphone-based methodology for head 3D model creation [4] and its accuracy has been evaluated by comparison with radiological imaging [5]. Reading the previous work is highly recommended for a better understanding of the current manuscript.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of Registration Methods for Cranial 3D Modelling

Barbero-García¹,

Lerma²

2019

The II Geomatics Engineering Conference

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Three-dimensional (3D) models are a useful tool for cranial deformation analysis in infants. The registration of the head 3D models to a known coordinate system is vital for the obtainment of parameters and indexes that quantify deformation. In this study, three registration methodologies have been tested based on the principal component analysis (PCA) without tie points, and PCA measuring manually two and three identified tie points. Results show that the approach using PCA plus three manually identified tie points provides enough accuracy for the given application.

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“…The models were created using a smartphone camera and Agisoft PhotoScan as described by the authors in a previous paper [4].…”

Section: Data Acquisitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Registration Methods for Cranial 3D Modelling

Barbero-García¹,

Lerma²

2019

The II Geomatics Engineering Conference

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“…Smartphone video (more specifically slow‐motion video) is a useful tool for acquiring large numbers of images, suitable even for fast moving objects. These images can be used for the creation of 3D models of moving objects (Barbero‐García et al., ). With an image acquisition speed of 240 frames per second (fps) of many smartphones (still far below the ultra‐high‐speed cameras that reach up to 2000 fps), the computational cost is the main limitation given the number of images to be used for 3D modelling.…”

Section: Introductionmentioning

confidence: 99%

Smartphone‐based close‐range photogrammetric assessment of spherical objects

Barbero-García

Cabrelles

Lerma

et al. 2018

The Photogrammetric Record

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Smartphones have widened the possibilities for low-cost close-range image acquisition for three-dimensional (3D) modelling. They allow the rapid acquisition of large amounts of data for a wide range of applications. However, the accuracy of the models and the automation possibilities depend on the image acquisition conditions and application requirements. In this study, the accuracy and reliability of the derived photogrammetric 3D models are evaluated on a spherical set-up for close-range applications (c.30 cm). Different numbers of images, network configurations, targets, devices and camera calibration methodologies are tested and evaluated. Results show that for this close-range application high accuracy (0Á2 mm) and reliability can be achieved. The number of images did not significantly affect the accuracy but was vital for tie-point detection and image orientation. The use of artificial targets was found to be the key factor in increasing the final accuracy. In contrast, the image calibration strategy and the characteristics of the imaging device did not have a great impact on the results.Smartphone video (more specifically slow-motion video) is a useful tool for acquiring large numbers of images, suitable even for fast moving objects. These images can be used for the creation of 3D models of moving objects (Barbero-Garc ıa et al., 2017). With an image acquisition speed of 240 frames per second (fps) of many smartphones (still far below the ultra-high-speed cameras that reach up to 2000 fps), the computational cost is the main limitation given the number of images to be used for 3D modelling.Despite their advantages, smartphone cameras present high internal instability that hampers their correct calibration. This problem is common to all non-metric digital cameras (Fraser, 2013), but is especially exacerbated when working with smartphones. The radiometric accuracy of smartphone cameras is lower than that of single-lens reflex (SLR) cameras but, despite their limitations, studies have concluded that these cameras can be used for photogrammetric tasks with a required accuracy of 1:10 000 (Akca and Gruen, 2009).The development of useful tools, which could allow non-expert users to obtain accurate 3D models for different purposes, requires a high degree of automation (Remondino et al., 2014). However, most of the available automatic low-cost solutions provide low repeatability and reliability (Remondino et al., 2012). The development of fully automatic and reliable solutions for specific applications requires an extensive knowledge of the factors affecting the quality of the 3D models created using smartphones or other similar imaging devices, such as tablets. The most important factors include the determination of the ideal geometric network, the selection of the best video frames and their optimal number, as well as the accuracy requirements for camera calibration. These parameters can vary greatly depending on the characteristics and limitations of the image acquisition process for a specific application (suc...

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“…The possibilities of a low-cost, non-invasive, smartphone based photogrammetric tool for cranial deformation analysis are presented in other studies (Barbero-García et al 2017). Slow-motion videogrammetry recorded with a smartphone allows the quick acquisition of wellfocused images of the moving infants in real clinical conditions.…”

Section: Introductionmentioning

confidence: 99%

“…The images are later used to create 3D models for analysis of cranial deformation in an accurate, repeatable, low-cost and non-invasive way. Barbero-García et al (2017) presented the calculation of differences to an ideal head, represented by an adjusted three-axis ellipsoid. The methodology has been pointed as an interesting option for cranial deformation, but its accuracy and repeatability are still being studied.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Repeatability on Videogrammetry for Infants’ Cranial Deformation

García¹,

Lerma²,

Mateu³

et al. 2017

Proceedings - 1st Congress in Geomatics Engineering - CIGeo

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Abstract:Cranial deformation affects a large number of infants. The methodologies commonly employed to measure the deformation include, among others, calliper measurements and visual assessment for mild cases and radiological imaging for severe cases, where surgical intervention is considered. Visual assessment and calliper measurements usually lack the required level of accuracy to evaluate the deformation. Radiological imaging, including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), are costly and highly invasive. The use of smartphones to record videos that can be used for three-dimensional (3D) modelling of the head has emerged as a low-cost, noninvasive methodology to extract 3D information of the patient. To be able to analyse the deformation, a novel technique is employed: the obtained model is compared with an ideal head. In this study we have tested the repeatability of the process. For this purpose, several models of two patients have been obtained and the differences between them are evaluated. The results show that the differences in the ellipsoid semiaxis for the same patient are usually below 4 mm, although they increase up to 6.4 mm in some cases. The variability in the distances to the ideal head, which are the values used to evaluate deformity, reaches a maximum value of 2.7 mm. The errors obtained are comparable to those of classical measurement techniques and show the potential of the methodology in development.Keywords: Photogrammetry, Low-cost, Plagiocephaly, 3D modelling Resumen:La deformación craneal afecta a un elevado porcentaje de lactantes, a pesar de esto, no existen estándares para su medición. Existen diversas metodologías empleadas para el análisis de este tipo de deformación, que van desde el análisis visual o la medición con calibre en casos leves, a pruebas radiológicas en casos más graves, en los que se plantea la posibilidad de una intervención quirúrgica. El análisis visual y la medición con calibre a menudo carecen de la precisión requerida para evaluar la deformación, mientras que las pruebas radiológicas (Tomografía Axial Computarizada, TAC, o Resonancia Magnética, RM) son altamente invasivas y tienen un alto coste. Otras soluciones como la fotografía tridimensional (3D) incluyen complejos sistemas de varias cámaras, lo que también supone un coste elevado. La posibilidad de utilizar videos tomados con teléfonos inteligentes para la creación de modelos 3D craneales se ha convertido en una posibilidad para obtener información 3D del paciente de forma precisa y con un coste bajo. Para analizar la deformación se ha planteado una metodología que consiste en calcular las distancias entre el modelo generado y una forma craneal ideal. En este estudio se ha llevado a cabo el análisis de la repetibilidad del proceso de obtención del modelo y de la cabeza ideal ajustada, para ello se han obtenido varios modelos 3D de dos pacientes y se han evaluado las diferencias entre ellos. Los resultados muestran unas diferencias en los semiejes de los elipsoides de aproximadamen...

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Low-Cost Smartphone-Based Photogrammetry for the Analysis of Cranial Deformation in Infants

Cited by 50 publications

References 16 publications

Assessment of Registration Methods for Cranial 3D Modelling

Assessment of Registration Methods for Cranial 3D Modelling

Smartphone‐based close‐range photogrammetric assessment of spherical objects

Analysis of Repeatability on Videogrammetry for Infants’ Cranial Deformation

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