Reset filters

Search publications


By keyword
By department

No publications found.

 

High-Dynamic-Range Ultrasound: Application for Imaging Tendon Pathology.

Authors: Xiao YBoily MHashemi HSRivaz H


Affiliations

1 PERFORM Centre, Concordia University, Montreal, Quebec, Canada; Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada. Electronic address: yiming.xiao@concordia.ca.
2 Department of Diagnostic Radiology, McGill University, Montreal, Quebec, Canada.
3 Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada.
4 PERFORM Centre, Concordia University, Montreal, Quebec, Canada; Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada.

Description

High-Dynamic-Range Ultrasound: Application for Imaging Tendon Pathology.

Ultrasound Med Biol. 2018 07;44(7):1525-1532

Authors: Xiao Y, Boily M, Hashemi HS, Rivaz H

Abstract

Raw ultrasound (US) signal has a very high dynamic range (HDR) and, as such, is compressed in B-mode US using a logarithmic function to fit within the dynamic range of digital displays. However, in some cases, hyper-echogenic tissue can be overexposed at high gain levels with the loss of hypo-echogenic detail at low gain levels. This can cause the loss of anatomic detail and tissue texture and frequent and inconvenient gain adjustments, potentially affecting the diagnosis. To mitigate these drawbacks, we employed tone mapping operators (TMOs) in HDR photography to create HDR US. We compared HDR US produced from three different popular TMOs (Reinhard, Drago and Durand) against conventional US using a simulated US phantom and in vivo images of patellar tendon pathologies. Based on visual inspection and assessments of structural fidelity, image entropy and contrast-to-noise ratio metrics, Reinhard and Drago TMOs substantially improved image detail and texture.

PMID: 29628224 [PubMed - indexed for MEDLINE]


Links

PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29628224?dopt=Abstract