Effect of Using Tungsten-Anode X-Ray Tubes on Dose and Image Quality in Full-Field Digital Mammography

2008 ◽  
pp. 522-529 ◽  
Author(s):  
Jennifer M. Oduko ◽  
Kenneth C. Young ◽  
Ozcan Gundogdu ◽  
Abdulaziz Alsager
Keyword(s):  
Image Quality ◽  
Digital Mammography ◽  
Full Field ◽  
X Ray ◽  
Full Field Digital Mammography ◽  
Tungsten Anode

scholarly journals Image Quality Assessment via Segmentation of Breast Lesion in X-ray and Ultrasound Phantom Images from Fischer's Full Field Digital Mammography and Ultrasound (FFDMUS) System

2005 ◽  
Vol 4 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Jasjit Suri ◽  
Yujun Guo ◽  
Cara Coad ◽  
Tim Danielson ◽  
Idris Elbakri ◽  
...  
Keyword(s):  
Image Quality ◽  
Digital Mammography ◽  
Lesion Detection ◽  
Average Error ◽  
Ultrasound Images ◽  
Lesion Segmentation ◽  
Full Field ◽  
X Ray ◽  
Full Field Digital Mammography ◽  
The Mean

Fischer has been developing a fused full-field digital mammography and ultrasound (FFDMUS) system funded by the National Institute of Health (NIH). In FFDMUS, two sets of acquisitions are performed: 2-D X-ray and 3-D ultrasound. The segmentation of acquired lesions in phantom images is important: (i) to assess the image quality of X-ray and ultrasound images; (ii) to register multi-modality images; and (iii) to establish an automatic lesion detection methodology to assist the radiologist. In this paper we developed lesion segmentation strategies for ultrasound and X-ray images acquired using FFDMUS. For ultrasound lesion segmentation, a signal-to-noise (SNR)-based method was adapted. For X-ray segmentation, we used gradient vector flow (GVF)-based deformable model. The performance of these segmentation algorithms was evaluated. We also performed partial volume correction (PVC) analysis on the segmentation of ultrasound images. For X-ray lesion segmentation, we also studied the effect of PDE smoothing on GVF's ability to segment the lesion. We conclude that ultrasound image qualities from FFDMUS and Hand-Held ultrasound (HHUS) are comparable. The mean percentage error with PVC was 4.56% (4.31%) and 6.63% (5.89%) for 5 mm lesion and 3 mm lesion respectively. The mean average error from the segmented X-ray images with PDE yielded an average error of 9.61%. We also tested our program on synthetic datasets. The system was developed for Linux workstation using C/C++.

scholarly journals Visualization of Breast Microcalcifications on Digital Breast Tomosynthesis and 2-Dimensional Digital Mammography Using Specimens

2017 ◽  
Vol 11 ◽  
pp. 117822341770338 ◽  
Author(s):  
Jieun Byun ◽  
Jee Eun Lee ◽  
Eun Suk Cha ◽  
Jin Chung ◽  
Jeoung Hyun Kim
Keyword(s):  
Image Quality ◽  
Digital Mammography ◽  
Digital Breast Tomosynthesis ◽  
Kappa Statistic ◽  
Breast Tomosynthesis ◽  
Full Field ◽  
Full Field Digital Mammography ◽  
Better Than

Purpose: The purpose of this study is to compare the visibility of microcalcifications of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) using breast specimens. Materials And Methods: Thirty-one specimens’ DBT and FFDM were retrospectively reviewed by four readers. Results: The image quality of microcalcifications of DBT was rated as superior or equivalent in 71.0% by reader 1, 67.8% by reader 2, 64.5% by reader 3, and 80.6% by reader 4. The Fleiss kappa statistic for agreement among readers was 0.31. Conclusions: We suggest that image quality of DBT appears to be comparable with or better than FFDM in terms of revealing microcalcifications.

Effective x-ray attenuation measurements with full field digital mammography

2006 ◽  
Vol 33 (11) ◽  
pp. 4350-4366 ◽  
Author(s):  
John J. Heine ◽  
Madhusmita Behera
Keyword(s):  
Digital Mammography ◽  
Full Field ◽  
X Ray ◽  
Full Field Digital Mammography
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