MO-FG-209-00: Recent Advances in Virtual Tools for Validation of 3D/4D Breast Imaging Systems (TG234)

2016 ◽  
Vol 43 (6Part31) ◽  
pp. 3715-3715
Author(s):  
Predrag Bakic ◽  
Kyle Myers
Keyword(s):  
Breast Imaging ◽  
Imaging Systems ◽  
Virtual Tools ◽  
Recent Advances

TU-A-17A-02: In Memoriam of Ben Galkin: Virtual Tools for Validation of X-Ray Breast Imaging Systems

2014 ◽  
Vol 41 (6Part26) ◽  
pp. 446-447 ◽  
Author(s):  
K Myers ◽  
P Bakic ◽  
C Abbey ◽  
M Kupinski ◽  
T Mertelmeier
Keyword(s):  
Breast Imaging ◽  
Imaging Systems ◽  
X Ray ◽  
Virtual Tools ◽  
In Memoriam

MO-A-141-02: Session In Memory of Fearghus O't Foghludha - Virtual Tools for Validation of X-Ray Breast Imaging Systems

2013 ◽  
Vol 40 (6Part23) ◽  
pp. 390-390 ◽  
Author(s):  
P Bakic ◽  
K Myers ◽  
I Reiser ◽  
N Kiarashi ◽  
R Zeng
Keyword(s):  
Breast Imaging ◽  
Imaging Systems ◽  
X Ray ◽  
Virtual Tools

scholarly journals Deep learning in holography and coherent imaging

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Yair Rivenson ◽  
Yichen Wu ◽  
Aydogan Ozcan
Keyword(s):  
Deep Learning ◽  
Image Reconstruction ◽  
Imaging Systems ◽  
New Paradigm ◽  
Coherent Imaging ◽  
Holographic Image ◽  
Engineering Research ◽  
Recent Advances ◽  
Reconstruction Methods ◽  
Recovery Techniques

Abstract Recent advances in deep learning have given rise to a new paradigm of holographic image reconstruction and phase recovery techniques with real-time performance. Through data-driven approaches, these emerging techniques have overcome some of the challenges associated with existing holographic image reconstruction methods while also minimizing the hardware requirements of holography. These recent advances open up a myriad of new opportunities for the use of coherent imaging systems in biomedical and engineering research and related applications.

BREAST IMAGING SYSTEMS: A REVIEW AND COMPARATIVE STUDY

2010 ◽  
Vol 10 (01) ◽  
pp. 5-34 ◽  
Author(s):  
S. VINITHA SREE ◽  
EDDIE Y.-K. NG ◽  
RAJENDRA ACHARYA U ◽  
WILLIAM TAN
Keyword(s):  
Biological Sciences ◽  
Survival Rate ◽  
Early Detection ◽  
Breast Imaging ◽  
Early Detection Of Cancer ◽  
Imaging Systems ◽  
Clinical Settings ◽  
Treatment Protocols ◽  
Physical Examinations ◽  
Human Illness

Due to the successful union between computational technologies and basic laws of physics and biological sciences, many biomedical imaging systems now find significant presence in clinical settings, aiding physicians in diagnosing most forms of human illness with more confidence. In the case of breast imaging, apart from the basic diagnosis, these imaging systems also help in locating the abnormal tissues for biopsy, identifying the exact margins of the lesion for good lumpectomy results, staging and restaging the cancer, detecting locations of metastases, and planning and following up treatment protocols. It is well known that early detection of cancer is the only way to increase the survival rate of the patient. Without such imaging systems, it would be hard and almost impossible for the physicians to determine the nature and extent of the disease by merely simple physical examinations and biopsies. This article presents a description of most of these invaluable breast-imaging systems. Moreover, a comparison of these modalities and a review of a few of the developments these devices have come across over the years are also given.

Breast Surface Estimation for Radar-Based Breast Imaging Systems

2008 ◽  
Vol 55 (6) ◽  
pp. 1678-1686 ◽  
Author(s):  
Trevor C. Williams ◽  
Jeff M. Sill ◽  
Elise C. Fear
Keyword(s):  
Breast Imaging ◽  
Imaging Systems ◽  
Surface Estimation

Study on the compromise between resolution and attenuation for breast imaging systems

2017 ◽  
Author(s):  
S. Di Meo ◽  
A. Martellosio ◽  
M. Pasian ◽  
M. Bozzi ◽  
L. Perregrini ◽  
...  
Keyword(s):  
Breast Imaging ◽  
Imaging Systems

scholarly journals Microwave Breast Imaging System Prototype with Integrated Numerical Characterization

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Mark Haynes ◽  
John Stang ◽  
Mahta Moghaddam
Keyword(s):  
Breast Imaging ◽  
Imaging System ◽  
Current Model ◽  
Imaging Systems ◽  
Simple Test ◽  
Ansoft Hfss ◽  
Numerical Characterization ◽  
Microwave Breast Imaging ◽  
System Prototype ◽  
Test Objects

The increasing number of experimental microwave breast imaging systems and the need to properly model them have motivated our development of an integrated numerical characterization technique. We use Ansoft HFSS and a formalism we developed previously to numerically characterize anS-parameter- based breast imaging system and link it to an inverse scattering algorithm. We show successful reconstructions of simple test objects using synthetic and experimental data. We demonstrate the sensitivity of image reconstructions to knowledge of the background dielectric properties and show the limits of the current model.

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