Phase-based probabilistic active contour for nerve detection in ultrasound images for regional anesthesia

Hafiane, Adel; Vieyres, Pierre; Delbos, Alain

doi:10.1016/j.compbiomed.2014.06.001

Cited by 38 publications

(24 citation statements)

References 31 publications

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“…Very little research in the literature has addressed nerve segmentation. The PGVF method suggested in (Hafiane et al, 2014b), showed good results for the sciatic nerve, but it was less efficient for the median nerve as shown in Table 5. This result may be explained by the fact that US imaging of the forearm generates several regions similar to the nerve region, and the learning process used in PGVF was not sufficient to handle such a situation.…”

Section: Accepted Manuscriptmentioning

confidence: 92%

“…Regional anesthesia deals with different types of nerve tissues which have different appearance properties in the ultrasound images. Very few studies have focused on segmentation and detection problems for regional anesthesia (Thouin et al, 2011;Hafiane et al, 2014b;Hadjerci et al, 2014). For instance, in (Hafiane et al, 2014b), a method based on the combination of a A C C E P T E D M A N U S C R I P T monogenic signal and a probabilistic active contour was proposed to detect the sciatic nerve.…”

Section: Related Workmentioning

confidence: 98%

“…Very few studies have focused on segmentation and detection problems for regional anesthesia (Thouin et al, 2011;Hafiane et al, 2014b;Hadjerci et al, 2014). For instance, in (Hafiane et al, 2014b), a method based on the combination of a A C C E P T E D M A N U S C R I P T monogenic signal and a probabilistic active contour was proposed to detect the sciatic nerve. The technique proposed in (Hadjerci et al, 2014) was based on the combination of Median Binary Pattern (MBP) (Hafiane et al, 2008) and a Gabor filter to characterize and classify pixels belonging to the nerve tissues.…”

Section: Related Workmentioning

confidence: 98%

“…However, nerve segmentation needs another step to obtain the nerve boundaries. For that purpose, we used the phase-based probabilistic active contour to segment the nerve(Hafiane et al, 2014b), since it provides better results for nerve segmentation compared to the classical ones. The bounding box of the localization is used as an initial contour.This method uses the parametric active contour with a modified energy function of the Gradient Vector Flow (GVF)(Xu and Prince, 1998).…”

mentioning

confidence: 99%

See 3 more Smart Citations

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

Hadjerci

Hafiane

Morette

et al. 2016

Expert Systems with Applications

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Section: Accepted Manuscriptmentioning

confidence: 92%

Section: Related Workmentioning

confidence: 98%

Section: Related Workmentioning

confidence: 98%

mentioning

confidence: 99%

See 2 more Smart Citations

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

Hadjerci

Hafiane

Morette

et al. 2016

Expert Systems with Applications

Self Cite

View full text Add to dashboard Cite

“…This approach involves the use of a linear filter (holding a homogeneous mask area) that is applied to minimize speckle noise. Similarly, in [21] the authors propose an approach based on active contours without considering a filtering step. Although promising results are obtained with sophisticated segmentation schemes, the above methodologies are not focused on speckle reduction.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of nerve structure segmentation by a correntropy-based pre-image approach

Gil-Gonzalez

Álvarez-Meza

Echeverry-Correa

et al. 2017

TecnoL.

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Peripheral Nerve Blocking (PNB) is a commonly used technique for performing regional anesthesia and managing pain. PNB comprises the administration of anesthetics in the proximity of a nerve. In this sense, the success of PNB procedures depends on an accurate location of the target nerve. Recently, ultrasound images (UI) have been widely used to locate nerve structures for PNB, since they enable a non-invasive visualization of the target nerve and the anatomical structures around it. However, UI are affected by speckle noise, which makes it difficult to accurately locate a given nerve. Thus, it is necessary to perform a filtering step to attenuate the speckle noise without eliminating relevant anatomical details that are required for high-level tasks, such as segmentation of nerve structures. In this paper, we propose an UI improvement strategy with the use of a pre-image-based filter. In particular, we map the input images by a nonlinear function (kernel). Specifically, we employ a correntropy-based mapping as kernel functional to code higher-order statistics of the input data under both nonlinear and non-Gaussian conditions. We validate our approach against an UI dataset focused on nerve segmentation for PNB. Likewise, our Correntropy-based Pre-Image Filtering (CPIF) is applied as a pre-processing stage to segment nerve structures in a UI. The segmentation performance is measured in terms of the Dice coefficient. According to the results, we observe that CPIF finds a suitable approximation for UI by highlighting discriminative nerve patterns.

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Development of probe control system and median nerve extraction in ultrasound images for 3D visualization

Katayama

Shibata

Sasaki

et al. 2018

Elect Comm in Japan

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In the diagnosis of peripheral nerve disorder such as carpal tunnel syndrome, the doctor and the scientific occupational therapist mainly narrow down the position of the lesion by function evaluation. The diagnosis has been decided by the evaluation of the electrophysiological nerve conduction characteristics. In addition to this, in recent years, it has become possible to observe the median nerve as a tomogram using an ultrasound diagnostic apparatus, so it is possible to check the thickness and shape of the median nerve without cutting the wrist joint part. However, in order to objectively observe a tissue having a three-dimensional structure such as a median nerve, it is required to obtain not only tomographic images of the median nerve but also threedimensional shape information. Therefore, in order to visualize the median nerve as the three-dimensional structure, we develop a device that mechanically manipulates an ultrasound probe, while operating an ultrasound probe, it takes photographs of the nerve tomographic images as well as it extracts the nerve from the images. In this paper, we describe the development of a device that operates an ultrasound probe and extract the median nerve in an ultrasound images. K E Y W O R D Smedian nerve, probe, ultrasound image, visualization Electron Comm Jpn. 2018;101:3-12.

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Phase-based probabilistic active contour for nerve detection in ultrasound images for regional anesthesia

Cited by 38 publications

References 31 publications

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

Enhancement of nerve structure segmentation by a correntropy-based pre-image approach

Development of probe control system and median nerve extraction in ultrasound images for 3D visualization

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