English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Ultrasound image analysis and recognition techniques for improving workflow in diagnosis and treatment are introduced. Fully automatic techniques for applications of cardiac plane extraction, fetal weight measurement, and ultrasound-CT image registration for liver surgery navigation are included. For standard plane extraction in 3D cardiac ultrasound, multiple cardiac landmarks defined in ultrasound cardiac examination guideline are detected and localized by a Hough Forest based detector, and six standard cardiac planes cardiac diagnosis are extracted following the guideline. For automatic fetal weight measurement, biparietal diameter (BPD), femur length (FL) and abdominal circumference (AC) are estimated by segmenting corresponding organs and regions from fetal ultrasound images. For ultrasound-CT liver image registration, initial alignment is obtained by localizing a corresponding portal vein branch from an intraoperative ultrasound and preoperative CT image pair. Then portal vein regions of the ultrasound-CT image pair are extracted by a machine learning method and are used for image registration.

Automatic Image Analysis and Recognition for Ultrasound Diagnosis and Treatment in Cardiac, Obstetrics and Radiology