Spine surface detection from local phase‐symmetry enhanced ridges in ultrasound images

Shajudeen, Peer Mohamed S.; Righetti, Raffaella

doi:10.1002/mp.12509

Cited by 12 publications

(11 citation statements)

References 38 publications

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“…US has been shown to complement radiography in imaging newly formed bone as well as several types of bone fractures and defects 14 , 15 , 17 , 31 , 46 , 47 . Availability of automatic bone surface detection techniques 33 , 34 , 48 can further extend the successful use of US in orthopedic applications. While a large body of past work concentrated on qualitative or semi-quantitative US evaluation 14 – 16 , 20 , there remains a lack of objective quantification tools to assess healing outcomes in early fracture stages.…”

Section: Discussionmentioning

confidence: 99%

“…For computation of the morphometric parameters to quantify the bulk, surface and contact of the new bone, knowledge of the new bone representation in US and CT together with knowledge of the shell is required. For detecting new bone in the US data, the B-mode images were pre-processed with noise suppression and bone surface enhancement techniques as in our previous study 34 . A method based on the 3-D phase symmetry (PS) 48 was then applied to identify the bone surface candidates.…”

Section: Methodsmentioning

confidence: 99%

“…5 . In each slice of the bone surface segmented from US, foreground areas were thinned and spurious branches were pruned 34 . In each column of the image, only the pixel with the lowest depth was kept to avoid ambiguity arising in partial occlusion (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, US-based bone morphometry would be easier to standardize and would more objectively reflect regeneration outcomes. While the use of US to assess regenerated new bone morphology is currently limited to semi-quantitative analysis 20 , previously-developed US-based bone surface detection techniques 33 , 34 may still be effective in detecting newly formed bone in 3-D. Such techniques could be coupled with markers of tissue morphometry to accurately quantify bone formation from the US data.…”

Section: Introductionmentioning

confidence: 99%

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Identification of ultrasound imaging markers to quantify long bone regeneration in a segmental tibial defect sheep model in vivo

Tang

Shajudeen

Tasciotti

et al. 2020

Sci Rep

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The healing of large bone defects has been investigated for decades due to its complexity and clinical relevance. Ultrasound (US) methods have shown promise in monitoring bone healing, but no quantitative method to assess regenerated bone morphology in US images has been presented yet. In this study, we investigate new US morphometric parameters to quantify bone regeneration in vivo . A segmental tibial defect was surgically created and stabilized in a sheep animal model. US and computed tomography (CT) imaging data were collected two months post-surgery. New bone was assessed, reconstructed and quantified from the US and CT data using 3 morphometric parameters: the new-bone bulk (NBB), new-bone surface (NBS) and new-bone contact (NBC). The distance (mm) between surface reconstructions from repeated US was and from US and CT was . In the mid-shaft of the defected tibia, US measurements of NBB, NBS and NBC were significantly higher than the corresponding CT measurements ( ). Based on our results, we conclude that US may complement CT to reconstruct and quantify bone regrowth, especially in its early stages.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification of ultrasound imaging markers to quantify long bone regeneration in a segmental tibial defect sheep model in vivo

Tang

Shajudeen

Tasciotti

et al. 2020

Sci Rep

Self Cite

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“…The model is done using Convolutional Neural Network (CNN) before the refinement of the registration using an orientation code mutual information metric. Shajudeen et al [22] developed a method for automatic segmentation of the spine bones surface in ultrasound images. The method can be extended to any bone surface presented in ultrasound images.…”

Section: Related Workmentioning

confidence: 99%

Spinal Cord Segmentation in Ultrasound Medical Imagery

et al. 2020

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In this paper, we study and evaluate the task of semantic segmentation of the spinal cord in ultrasound medical imagery. This task is useful for neurosurgeons to analyze the spinal cord movement during and after the laminectomy surgical operation. Laminectomy is performed on patients that suffer from an abnormal pressure made on the spinal cord. The surgeon operates by cutting the bones of the laminae and the intervening ligaments to relieve this pressure. During the surgery, ultrasound waves can pass through the laminectomy area to give real-time exploitable images of the spinal cord. The surgeon uses them to confirm spinal cord decompression or, occasionally, to assess a tumor adjacent to the spinal cord. The Freely pulsating spinal cord is a sign of adequate decompression. To evaluate the semantic segmentation approaches chosen in this study, we constructed two datasets using images collected from 10 different patients performing the laminectomy surgery. We found that the best solution for this task is Fully Convolutional DenseNets if the spinal cord is already in the train set. If the spinal cord does not exist in the train set, U-Net is the best. We also studied the effect of integrating inside both models some deep learning components like Atrous Spatial Pyramid Pooling (ASPP) and Depthwise Separable Convolution (DSC). We added a post-processing step and detailed the configurations to set for both models.

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Soft-tissue sound-speed-aware ultrasound-CT registration method for computer-assisted orthopedic surgery

Liu,

Wang,

Sun

et al. 2024

Med Biol Eng Comput

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Spine surface detection from local phase‐symmetry enhanced ridges in ultrasound images

Cited by 12 publications

References 38 publications

Identification of ultrasound imaging markers to quantify long bone regeneration in a segmental tibial defect sheep model in vivo

Identification of ultrasound imaging markers to quantify long bone regeneration in a segmental tibial defect sheep model in vivo

Spinal Cord Segmentation in Ultrasound Medical Imagery

Soft-tissue sound-speed-aware ultrasound-CT registration method for computer-assisted orthopedic surgery

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