Registration of RF ultrasound data using hybrid local binary patterns

Klein, Tassilo; Hansson, Mattias; Karamalis, Athanasios; Navab, Nassir

doi:10.1109/isbi.2012.6235744

Cited by 2 publications

(4 citation statements)

References 11 publications

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“…Globally, Hellinger distance between distributions is utilized and Fuzzy Local Binary Patterns (FLBP) is used on a local scale to perform registration. As a result, the median registration error on five datasets using the methodology put forth in [64] is much lower than other similarity measures such as SSD and NCC.…”

Section: Neckmentioning

confidence: 94%

“…A novel hybrid procedure for rigid registration was proposed in [64]. The novel similarity metric is based on Hellinger distance between the distributions in images on the global scale, and a statistics-based extension of Fuzzy Local Binary Patterns (FLBP) on a local scale.…”

Section: Novelmentioning

confidence: 99%

“…In [64], a novel hybrid procedure for registering envelop detected radio frequency ultrasound data of human neck was proposed, using global statistics and local textural features. Globally, Hellinger distance between distributions is utilized and Fuzzy Local Binary Patterns (FLBP) is used on a local scale to perform registration.…”

Section: Neckmentioning

confidence: 99%

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Ultrasound registration: A review

Che

Mathai

Galeotti

2017

Methods

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This article is a review of registration algorithms for use between ultrasound images (monomodal image-based ultrasound registration). Ultrasound is safe, inexpensive, and real-time, providing many advantages for clinical and scientific use on both humans and animals, but ultrasound images are also notoriously noisy and subject to several unique artifacts/distortions. This paper introduces the topic and unique aspects of ultrasound-to-ultrasound image registration, providing a broad introduction and summary of the literature and the field. Both theoretical and practical aspects are introduced. The first half of the paper is theoretical, organized according to the basic components of a registration framework, namely preprocessing, image-similarity metrics, optimizers, etc. It further subdivides these methods between those suitable for elastic (non-rigid) vs. inelastic (matrix) transforms. The second half of the paper is organized by anatomy and is practical in nature, presenting and discussing the complete published systems that have been validated for registration in specific anatomic regions.

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Section: Neckmentioning

confidence: 94%

Section: Novelmentioning

confidence: 99%

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Ultrasound registration: A review

Che

Mathai

Galeotti

2017

Methods

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“…Among the different metrics the authors used, they achieved 92% of the successful registration rate for the correlation ratio metric. In [9], a hybrid procedure was proposed using global statistics and local textural features to register envelope-detected radio frequency ultrasound data of the human neck and was shown to outperform standard measures such as the sum of absolute differences (SSD), normalized cross-correlation (NCC), and Hellinger distance. In [10], a fully automated deformable registration algorithm was developed using the Bayesian regularization framework to register free-hand ultrasound volumes of female breasts.…”

Section: A Ultrasound Registrationmentioning

confidence: 99%

Two-Step Rigid and Non-Rigid Image Registration for the Alignment of Three-Dimensional Echocardiography Sequences From Multiple Views

Shanmuganathan,

Noga,

Boulanger

et al. 2024

IEEE Access

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Ultrasound is a widely used imaging modality, which provides continuous real-time imaging of the human heart, brain, liver, and many other organs. Accurate cardiovascular evaluation plays an important role in early disease diagnosis. Real-time 3D echocardiography (RT3DE) imaging allows better three-dimensional (3D) imaging by extracting spatial features along with temporal information, thus improving clinical decision making. Although there have been technological advances, the majority of acquired RT3DE images tend to be of low quality, characterized by the absence of anatomical information, decreased spatial and temporal resolution, speckle noise, and a limited field of view (FOV). By registering RT3DE images obtained from several windows, it is possible to enhance the recognition of structures and achieve a substantial improvement in image quality as well as it is also useful in the fusion of echo images to image the entire heart. This study proposes a fully automatic point-based rigid registration technique, followed by nonrigid B-spline registration, to align four-dimensional (4D) echocardiogram images acquired from various sonographic windows. The methodology was evaluated using scans acquired from seven volunteers. The accuracy of registration was visually and quantitatively assessed by delineating the left ventricle in each scan and computing the Dice score overlap metric and the Hausdorff distance mutual proximity measure between the first scan and the rest. The overall findings demonstrate that the suggested registration method improves image alignment compared to the initial scans, which might be helpful in the fusion of echocardiographic images.

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Registration of RF ultrasound data using hybrid local binary patterns

Cited by 2 publications

References 11 publications

Ultrasound registration: A review

Ultrasound registration: A review

Two-Step Rigid and Non-Rigid Image Registration for the Alignment of Three-Dimensional Echocardiography Sequences From Multiple Views

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