Evaluation of clinical Full Field DigitalMammography with the Task-Specific-System-Model-Based Fourier (TSMF)             ...
Outline   Task specific evaluation methodology     Development     Benefits of using phantom for FFDM image     quality as...
Background: current FFDM evaluation                                     FFDM system                                     pe...
MotivationDevelop Fourier based                                    X-ray tube        Compression paddleevaluation methodol...
Assumptions   Linear system     No non-linear/adaptive image processing   Cyclostationary system     Stationary noise     ...
Phantom assembly  Inspired by the CDMAM  phantom      Same uniform background      Same HVL      Simulated signals  Unifor...
Clinical systemsSystem        GE Senograhe       Hologic Selenia              DSDetector      Indirect           DirectPix...
System schematic                   8   Haimo Liu: haimo.liu@fda.hhs.gov
Generalized Modulation Transfer Function (GMTF)   GMTF      The modulus of the Fourier transformation of the line      res...
Evaluation of scatter removal method (GE)                              MTF (x direction)                                  ...
GMTF (x direction) for two clinical systems                    GE                     11     Haimo Liu: haimo.liu@fda.hhs....
GMTF along the two axes                  12      Haimo Liu: haimo.liu@fda.hhs.gov
Generalized Normalized Noise Power Spectrum (GNNPS)  GNNPS     The square of the Fourier transformation of the system     ...
GNNPS (x direction) for two clinical systems                        14       Haimo Liu: haimo.liu@fda.hhs.gov
Hotelling observer SNR             GMTF2        Difference signal2                     2                         2       S...
Methodology validation – comparison between methods    Fourier based method with                GMTF 2 FT[ΔSs ]2          ...
Methodology validation                    17   Haimo Liu: haimo.liu@fda.hhs.gov
Contrast-Detail curve                                         Contrast-Detail                                         (CD)...
Contrast-Detail curve: system performance prediction                                CD curve at unit dose                 ...
Contrast-Detail curve: human performance prediction                             Human performance                         ...
Conclusions   Fourier based evaluation methodology for clinical FFDM      Provide more information of the system using pha...
Upcoming SlideShare
Loading in …5
×

Tsmf Methodology

395 views
342 views

Published on

Clinical Full Field Digital Mammography system performance evaluation

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
395
On SlideShare
0
From Embeds
0
Number of Embeds
7
Actions
Shares
0
Downloads
1
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Divide into chapters: 1. benefits of using phantom 2. comparison between two modes for GE 3. validation 4. application on HologicWhat I proposed to go in the paper, I need your opinion of how I should present the dataIn the end: title, coauthor list, how to present, which journalYour opinions and suggestions are welcome, as well as how should I present the data
  • Clinical trial: Sensitivity and specificity of the technology Pissano: 2008-10, FFDM Guidance More information, create model of system, predict performance for other settingsLink between image quality and diagnostic performanceIncluding phantom- extra information, getting steps closer to link image quality to diagonostic…Limited to specific settings- gagne’s & channelsThis figure shows the current FFDM evaluation methods. First, FFDM performance can be evaluated by running clinical trials, they are ……the clinical trials give the diagnostic performance of the system. However, it has been shown in the literature that there is a link between the diagnostic performance of the system and the image quality, therefore ppl developed methods for evaluating……to represent the diagnostic performance of the system.
  • Same order of the legendPut it in the beginningMake a link between MTF and SNR, mtf itself is not enough for image quality assessmentBetter explain the plots
  • Change yellow to sth else, change curve style
  • NPS does averaging
  • This plot shows the threshold detectability, or the threshold of detectable discs with specific radius and thickness for a given system setting. For example, if we pick up “this dashed red line”, it shows the threshold detectability when using image acquisition mode B for a given dose: 0.65 mGy. All the signals below this line can not be detected, and all the signals above this line can be detected. Here, 75% detection probability was used as the threshold, which is b between 50% and 100%, where 50% is ….different colors indicate three different exposures or doses, dashed lines are the mode B and solide lines are the mode A. notice that, for all three exposures, the mode a has better performance then mode B because the threshold value is lower. However, even though this difference is consistent, it is still not clear if this difference is signifancant. Error bars and confidance intervals will be estimated in the future research to determine if the difference is significant statistically.Empty squares and circles
  • Tsmf Methodology

    1. 1. Evaluation of clinical Full Field DigitalMammography with the Task-Specific-System-Model-Based Fourier (TSMF) SNR Haimo Liu Fischell Department of Bioengineering University of Maryland-College Park FDA CDRH OSEL/DIAM Haimo Liu: haimo.liu@fda.hhs.gov
    2. 2. Outline Task specific evaluation methodology Development Benefits of using phantom for FFDM image quality assessment Application on clinical systems GE Senographe DS Comparison between two image acquisition modes Validation of the method Hologic Selenia Conclusion 2 Haimo Liu: haimo.liu@fda.hhs.gov
    3. 3. Background: current FFDM evaluation FFDM system performance Clinical trials Mean pixel value, Fourier based Image based standard deviation method method Expensive, time consuming Detector based: Diff. signal MTF, NPSHuman observers: Pixel SNR Cov. matrix radiologists Limitations: No systemSuffer from model background DQEreader’s variability variability, signal Hotelling SNR shape and size Does not account for scatter, focal Large number spot unsharpness of images 3 Haimo Liu: haimo.liu@fda.hhs.gov
    4. 4. MotivationDevelop Fourier based X-ray tube Compression paddleevaluation methodologyfor clinical FFDM systems Entire FFDM image acquisition With phantom that models breast attenuation Objective, task based Practical, collection of limited number of images Empirical model of the system, results not limited to specific settings Detector Computer console 4 Haimo Liu: haimo.liu@fda.hhs.gov
    5. 5. Assumptions Linear system No non-linear/adaptive image processing Cyclostationary system Stationary noise Shift-invariant system transfer function Infinite detector area 5 Haimo Liu: haimo.liu@fda.hhs.gov
    6. 6. Phantom assembly Inspired by the CDMAM phantom Same uniform background Same HVL Simulated signals Uniform PMMA plates Four 1 cm plates Aluminum plate 0.5 mm thick Model the Aluminum base (where signals are attached to) of the CDMAM phantom 6 Haimo Liu: haimo.liu@fda.hhs.gov
    7. 7. Clinical systemsSystem GE Senograhe Hologic Selenia DSDetector Indirect DirectPixel size 0.1mm ×0.1mm 0.07mm ×0.07mmKvp 30 30Target/Filt Mo/Mo Mo/MoerImage A:Fine View Mode Phantom Modeacquisition B:Standard ModemodeGrid Linear Cross-hatch grid 7 Haimo Liu: haimo.liu@fda.hhs.gov
    8. 8. System schematic 8 Haimo Liu: haimo.liu@fda.hhs.gov
    9. 9. Generalized Modulation Transfer Function (GMTF) GMTF The modulus of the Fourier transformation of the line response function measured within the breast phantom Five images of a copper edge placed between the PMMA plates Three detector entrance exposures Convert to mean glandular doses 2D GMTF Spline interpolation between 1D profiles along the two axes X direction: parallel to chest wall Y direction: perpendicular to chest wall 9 Haimo Liu: haimo.liu@fda.hhs.gov
    10. 10. Evaluation of scatter removal method (GE) MTF (x direction) 100 mAs, x-direction Without phantom System without grid gives better performance GMTF(x direction) 100 mAs, x-direction With phantom placed in the FOV System with grid gives better performance 10 Haimo Liu: haimo.liu@fda.hhs.gov
    11. 11. GMTF (x direction) for two clinical systems GE 11 Haimo Liu: haimo.liu@fda.hhs.gov
    12. 12. GMTF along the two axes 12 Haimo Liu: haimo.liu@fda.hhs.gov
    13. 13. Generalized Normalized Noise Power Spectrum (GNNPS) GNNPS The square of the Fourier transformation of the system noise measured at the center of the breast phantom Five images of the background phantom Three detector entrance exposures Convert to mean glandular doses 13 Haimo Liu: haimo.liu@fda.hhs.gov
    14. 14. GNNPS (x direction) for two clinical systems 14 Haimo Liu: haimo.liu@fda.hhs.gov
    15. 15. Hotelling observer SNR GMTF2 Difference signal2 2 2 Simulated gold disc signals inspired by the CDMAM phantomSNR² = GNNPS 15 Haimo Liu: haimo.liu@fda.hhs.gov
    16. 16. Methodology validation – comparison between methods Fourier based method with GMTF 2 FT[ΔSs ]2 SNR = simulated signals (Ss): GNNPS Phantom Image based method (image based signal: SI): SNR = ΔS I T K -1ΔS I Fourier based method with FT[ΔSI ]2 phantom image based signals, SNR = GNNPS ROI size 256×256: GNNPS256 256 Fourier based method with FT[ΔSI ]2 phantom image based signals, SNR = GNNPS ROI size 19×19: GNNPS19 19 16 Haimo Liu: haimo.liu@fda.hhs.gov
    17. 17. Methodology validation 17 Haimo Liu: haimo.liu@fda.hhs.gov
    18. 18. Contrast-Detail curve Contrast-Detail (CD) curve Four alternative forced choice (4 AFC) task Link SNR to detection probability 62.5% detection probability as the threshold Threshold thickness Generate CD curve 18 Haimo Liu: haimo.liu@fda.hhs.gov
    19. 19. Contrast-Detail curve: system performance prediction CD curve at unit dose SNR2 is linearly proportional to dose Normalize SNR by dose Normalize CD curve by dose Can be used to predict system performance Two clinical systems Different noise and deterministic properties Identical CD curves 19 Haimo Liu: haimo.liu@fda.hhs.gov
    20. 20. Contrast-Detail curve: human performance prediction Human performance prediction (GE Senographe DS) SNR 2 Human FHuman 2 30% 5% SNR TSMF TSMF CD curve at 51 μGy TSMF CD curve (adjusted by human efficiency) at 51 μGy Human CD curve at 70 μGy (GE Senographe 2000D) Human CD curve at 140 μGy (GE Senographe 2000D) 20 Haimo Liu: haimo.liu@fda.hhs.gov
    21. 21. Conclusions Fourier based evaluation methodology for clinical FFDM Provide more information of the system using phantom Scatter from the phantom Focal spot unsharpness Magnification Create a model of the system Not limited to specific system settings Predict system performance Get closer to link image quality to diagnostic performance of the system Clinical application GE Senographe Hologic Selenia 21 Haimo Liu: haimo.liu@fda.hhs.gov

    ×