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Adaptive median binary patterns for fully automatic nerves tracking in ultrasound images.

Abstract：

BACKGROUND AND OBJECTIVE:In the last decade, Ultrasound-Guided Regional Anesthesia (UGRA) gained importance in surgical procedures and pain management, due to its ability to perform target delivery of local anesthetics under direct sonographic visualization. However, practicing UGRA can be challenging, since it requires high skilled and experienced operator. Among the difficult task that the operator can face, is the tracking of the nerve structure in ultrasound images. Tracking task in US images is very challenging due to the noise and other artifacts. METHODS:In this paper, we introduce a new and robust tracking technique by using Adaptive Median Binary Pattern(AMBP) as texture feature for tracking algorithms (particle filter, mean-shift and Kanade-Lucas-Tomasi(KLT)). Moreover, we propose to incorporate Kalman filter as prediction and correction steps for the tracking algorithms, in order to enhance the accuracy, computational cost and handle target disappearance. RESULTS:The proposed method have been applied on real data and evaluated in different situations. The obtained results show that tracking with AMBP features outperforms other descriptors and achieved best performance with 95% accuracy. CONCLUSIONS:This paper presents the first fully automatic nerve tracking method in Ultrasound images. AMBP features outperforms other descriptors in all situations such as noisy and filtered images.

journal_name

Comput Methods Programs Biomed

journal_title

Computer methods and programs in biomedicine

authors

Alkhatib M,Hafiane A,Tahri O,Vieyres P,Delbos A

doi

10.1016/j.cmpb.2018.03.013

subject

Has Abstract

pub_date

2018-07-01 00:00:00

pages

129-140

eissn

0169-2607

issn

1872-7565

pii

S0169-2607(17)30906-9

journal_volume

160

pub_type

杂志文章

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