Automatic estimate of back anatomical landmarks and 3D spine curve from a Kinect sensor

Bonnet, Vincent; Yamaguchi, Takazumi; Dupeyron, Arnaud; Andary, Sebastien; Seilles, Antoine; Fraisse, Philippe; Venture, Gentiane

doi:10.1109/biorob.2016.7523746

Cited by 12 publications

(6 citation statements)

References 13 publications

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“…From the literature [15,16], it is known that there are a few prominent anatomical landmarks that are preserved from patient to patient, including the scapular spines and posterior superior iliac spines (PSIS). In contrast to the scapular spines, the PSIS have a depth that is weakly influenced by the spinal deformity.…”

Section: Reproducibility Of Acquired Datamentioning

confidence: 99%

“…A parameter that accurately detects and quantifies this right/left asymmetry from the surface point cloud data of the patient's back was therefore sought. After studying parameters proposed by different studies [13][14][15][16], a surface asymmetry parameter based on the area under the surface curve z(x) was selected. This parameter can be defined according to the following steps, illustrated in Figure 5.…”

Section: Definition Of the Surface Asymmetry Parametermentioning

confidence: 99%

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Preliminary Study for the Development of an Automatic Evaluation Tool of the Idiopathic Scoliosis Based on a 3D Point Cloud Captured by a Depth Camera

Calla¹,

Tomaszewski²,

Henry³

et al. 2022

MMC_C

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Idiopathic scoliosis is a tri-dimensional deformation of the spine of unknown causes, impacting 2 to 3% of the population. It's a chronic pathology starting during childhood or adolescence and it is associated to long term physical and psychological prejudices for the patient, leading to important healthcare costs for the system. The weight of these consequences is linked to the early diagnostic of the pathology and to the subsequent treatment. Therefore, the early screening of AIS is of major importance. In France, the actual screening technique is clinical (Adam's test), it's a technique reserved to personnel of the medical field and with an imperfect sensibility (71-84% depending on the literature). The final goal of our study is to develop a non-ionizing, automatic evaluation tool of the idiopathic scoliosis, that would allow an accurate screening and if possible to evaluate its severity. The preliminary work conducted with this goal is presented in this paper. After a first literature review concerning the idiopathic scoliosis, the depth camera Microsoft Kinect V2 is used to generate a tridimensional point cloud of the back's surface of the patient. This point cloud is computed with the objective of quantifying an asymmetry of the patient's back, indicator of the spine's deformation in the axial plan, a specificity of the scoliosis. The two main axes of work were about the guarantee of the data's reproducibility and the choice of a pertinent parameter for the back's surface asymmetry, based on clinical and physio-pathological hypotheses and on the available literature data. The outcome of this preliminary work is a novelty surface parameter acquired in a patient-related coordinate system, with the goal to maximize its reproducibility. The first results on a few healthy patients and a scoliotic patient were encouraging. This work will obviously need to be followed by a validation study on a larger cohort of healthy and scoliotic patient. A key objective in recommending assistive technologies is to promote personal independence, social participation and life-building.

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Section: Reproducibility Of Acquired Datamentioning

confidence: 99%

Section: Definition Of the Surface Asymmetry Parametermentioning

confidence: 99%

Preliminary Study for the Development of an Automatic Evaluation Tool of the Idiopathic Scoliosis Based on a 3D Point Cloud Captured by a Depth Camera

Calla¹,

Tomaszewski²,

Henry³

et al. 2022

MMC_C

View full text Add to dashboard Cite

show abstract

“…Therefore, we construct a graph structure over the relative minima, and knowing the starting and the ending point of the symmetry curve, we find the shortest path between them which then corresponds to the objective back symmetry curve. The starting and the ending point of the symmetry curve can be detected automatically by finding distinctive anatomical landmarks (C7 and S1/S3 or a midline point between lumbar dimples) [36,37], by placing markers on the patient's back or manually after the 3D acquisition (hence "semi-"). The basic algorithm is explained in the text below and described by Algorithm 1.…”

Section: Detection Of the 3d Symmetry Curvementioning

confidence: 99%

3D sensing of back symmetry curve suited for dynamic analysis of spinal deformities

Đonlić

Petković

Peharec³

et al. 2018

Automatika

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This paper is focused on meeting the demands for better detection and evaluation of the spinal deformities that go beyond a basic static 3D analysis. It is expected that by observing the spine while it moves an improved 3D deformity analysis and measurements can be achieved. In this paper, we present a novel approach for the automatic back symmetry curve sensing. Our approach can be used in the back shape analysis of many different positions, i.e. segments of the dynamic motion, and is not limited only to the upright standing position. The proposed method is based on the 3D surface reconstruction, surface curvature analysis and graph theoretic approach for the (semi-)automatic detection of the symmetry curve. In addition, we introduce a 3D scanning system which was used in our experiment to successfully generate 3D back surface reconstructions for each frame of the captured forward bending motion. We also tested the proposed method on the data collected using commercial 3D spine analysis system and the results were comparable. The additional experiment focusing on the dynamic analysis demonstrated that the proposed method can enable further advances in the automatic 3D back surface analysis by tracking the spine position throughout performed movements.

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“…With the advances in modern 3D imaging systems, this topic has experienced a recent revival, especially for low-cost consumer 3D capturing systems such as Kinect from Microsoft, Xtion Pro from ASUS, Intel D415 from Intel, Orbbec Astra from Orbbec, and many more. Kinect was proposed and used to obtain the spinous process line and spine midline [7][8][9]. The methods that the authors used are Sensors 2023, 23, 7808 2 of 14 based on a back shape curvature analysis, i.e., Gaussian curvature and mean curvature, and the anatomical landmarks used to estimate the spine midline are characterized by specific trunk surface curvature.…”

Section: Introductionmentioning

confidence: 99%

Minimal Required Resolution to Capture the 3D Shape of the Human Back—A Practical Approach

Kaiser,

Brusa,

Wyss

et al. 2023

Sensors

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Adolescent idiopathic scoliosis (AIS) is a prevalent musculoskeletal disorder that causes abnormal spinal deformities. The early screening of children and adolescents is crucial to identify and prevent the further progression of AIS. In clinical examinations, scoliometers are often used to noninvasively estimate the primary Cobb angle, and optical 3D scanning systems have also emerged as alternative noninvasive approaches for this purpose. The recent advances in low-cost 3D scanners have led to their use in several studies to estimate the primary Cobb angle or even internal spinal alignment. However, none of these studies demonstrate whether such a low-cost scanner satisfies the minimal requirements for capturing the relevant deformities of the human back. To practically quantify the minimal required spatial resolution and camera resolution to capture the geometry and shape of the deformities of the human back, we used multiple 3D scanning methodologies and systems. The results from an evaluation of 30 captures of AIS patients and 76 captures of healthy subjects showed that the minimal required spatial resolution is between 2 mm and 5 mm, depending on the chosen error tolerance. Therefore, a minimal camera resolution of 640 × 480 pixels is recommended for use in future studies.

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Automatic estimate of back anatomical landmarks and 3D spine curve from a Kinect sensor

Cited by 12 publications

References 13 publications

Preliminary Study for the Development of an Automatic Evaluation Tool of the Idiopathic Scoliosis Based on a 3D Point Cloud Captured by a Depth Camera

Preliminary Study for the Development of an Automatic Evaluation Tool of the Idiopathic Scoliosis Based on a 3D Point Cloud Captured by a Depth Camera

3D sensing of back symmetry curve suited for dynamic analysis of spinal deformities

Minimal Required Resolution to Capture the 3D Shape of the Human Back—A Practical Approach

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