2008 January DAI News - Carl E Ravin Advanced Imaging

DAI News
January 2008
A Newsletter of the Duke Advanced Imaging Laboratories
Editorial: To collaborate or not to collaborate? That is the question.
It is a pleasure to see the third issue of DAI News taking shape. This newsletter is proving to be a
good vehicle to take stock, consolidate, and celebrate our accomplishments on an annual basis.
Reading through these newsletters, I have personally been much encouraged to learn about the
extent and reach of our collective academic enterprise. Thank you for all that you do. It is truly a
privilege for me to work among such distinguished scientists and friends.
This Issue
Editorial
New Faculty
Research Updates
Awards & Honors
New Publications
Focus on Research
Alumni News
Other News
Arrivals/Departures
Editors:
Nicole Ranger
Ehsan Samei
In reviewing our accomplishments of the last year, I would venture to say that probably none of these
would have been possible if we had tried to work independently, in our individual “cubicles.”
Working independently can be quite attractive in many respects. To name only a few advantages, you
are in full control, do not have the hassle of negotiating, and do not have to wait for anybody else.
But then (and that is the rub), you can only go so far and do so much. In all likelihood, sooner or
later, you will face a formidable obstacle that is beyond your personal resources, and that will send
you back to square one. You find you have to collaborate, with a colleague in the next cubicle, or
the next building, or the next state. But how? In my own short academic life, I have experienced or
witnessed numerous bad collaborations, many good ones, but also a few that I would put into the
“horror” category. What is it that makes a collaboration good? I want to share here just a few
pointers from my experience, with the hope that they might be of some value to you. These are not
comprehensive. I claim no expertise, and accept no liabilities. Use at your own risk!
First of all, keep in mind that collaboration is “expensive.” It is expensive in terms of your time,
attention, and working efficiency. Having to communicate takes time, especially if you are
communicating with a person who is not a friend and is not in your field. Therefore, you need to be
judicious and purposeful in all your collaborations. Not all collaborations are worth the effort.
Second, be clear about why you collaborate. Is it for a critical resource that you need, or a critical
piece of advice that can get you out of deadlock, or is it just that you want to be collegial? These
are all good reasons, but in my experience it does not pay to collaborate just because you want to
collaborate. A superfluous collaboration will serve no one. Third, aim to communicate effectively.
Go out of your way to see “eye to eye” with your collaborator. Make clear who needs exactly what by
when, and what are the expectations in terms of writing and authorship. Aim to reach a common
understanding at the front end of collaboration, not at the end. Ambiguous arrangements lead to
unconfirmed expectations, which lead to frustration, which makes the collaboration even more
“expensive.” Needless to say, if you make a promise, make sure to deliver, and if you are delayed,
explain (before the due date) why and for how long. Delays are expected; a lack of communication is
not. Finally, keep in mind that a good collaboration is something that you add to your research
“repertoire.” You can always go back at a later date to the same person and initiate another fruitful
collaboration. So, anticipate and strive to leave a collaboration with fruitful outcome and your
collaborator as a friend. There is more at stake than the project at hand.
Ehsan Samei, Director
New Faculty: Qiang Li, PhD
DAI Labs is pleased to welcome Dr. Qiang Li, who recently joined the DAI Labs faculty in Jan 2008.
Qiang obtained his B.E. in Electrical Engineering in 1983 from the Xi’an Jiaotong University in China,
his M.E. in Computer Science in 1986 from Huazhong University of Science and Technology in China
and his PhD in Electronics and Information Science in 1998 from the Kyoto Institute of Technology in
Japan. In 1998 Dr. Li joined the Department of Radiology at the University of Chicago as a Research
Associate in the laboratory of Dr. Kunio Doi and was promoted to Assistant Professor there in 2001.
In the past ten years, Dr. Li has been a co-author of 39 peer-reviewed journal papers (16 as senior
author), an inventor of 7 U.S. patents, and the PI of an NIH R01 grant. The CAD techniques developed
by Dr. Li and colleagues have been licensed to GE Medical Systems, Toshiba Medical Systems, R2
Technology (Hologic), Riverain Medical Group, and Mitsubishi Space Software Corporation. See Focus
on Research pg. 4.
For more information contact: li.qiang@duke.edu
Research Updates:
 For the breast tomosynthesis project, led by Dr. Joseph Lo, we have renewed a 2-year research agreement with
Siemens Medical Solutions. In conjunction with the NIH R01 grant which is now in its 2nd of 4 years, we will continue
work on optimization of radiographic technique and acquisition, as well as development of reconstruction algorithms,
visualization, computer aided detection, and contrast enhanced breast tomosynthesis. The clinical trial has now
successfully accrued 241 subjects. We have already made a big difference in the lives of two women, whose breast
cancer was missed by conventional mammography screening but thankfully detected at early stages by our research
tomosynthesis protocols. We are happy to report that both subjects have completed therapy and are doing well. One
of them gave a very moving talk at the October Breast Cancer Awareness Month activity, reminding us of the very
human reasons motivating our research.
 Dr. Samei, Amar Chawla and Sarah Boyce have completed the construction of the prototype acquisition system for
chest correlation and stereo imaging. The system is capable of acquiring multi-projection images from any verticalor horizontal-oblique orientation within a ±20 degree range. A clinical trial has commenced with over 45 human
subjects with confirmed subtle lung nodules already imaged. We have also installed a state-of-the-art hi-fidelity, 10
mega pixel, stereo display system at DAI Labs display lab to be used in the study.
 The evaluation of correlation imaging for breast applications (led by Dr. Samei and Amar Chawla) is advancing
with recent completion of a comprehensive optimization study pointing to optimum angular range and number of
projections independent of total dose.
 The pediatric CT project (led by Dr. Samei and Xiang Li in collaboration with Dr. Frush), is progressing with
completion of our nodule simulation protocol. An observer study has confirmed the simulated nodules are
perceptually indistinguishable from real lesions. A pilot study on the impact of dose on lesion detection has also just
been completed substantiating the potential for significant reduction of pediatric CT dose with minimal to no impact
on accuracy.
 Drs. Samei and Saunders are modeling a contrast enhanced dual energy tomosynthesis system to discover the
technique that provides maximum signal difference to noise adjusted for dose. This model will be verified using full
Monte Carlo techniques to account for scatter and detector degradation effects.
 The project on ambient lighting (led by Dr. Samei, Amar Chawla, and Ben Pollard) has moved to the next stage,
assessing the impact of ambient lighting on reading clinical chest radiographs and mammograms. Observer studies
with radiologists are currently underway.
 Dr. Lo and Victoria Seewaldt of the Dept of Medicine are co-PIs of a new grant from the US Army Breast Cancer
Research Program. The Synergistic Idea Award W81XWH-07-1-0393 entitled "Biologic and Computational Models of
Mammographic Density and Stromal Patterning” is funded from 7/1/07 to 7/31/09, total costs for both years is
$779,275. Only 25 of these prestigious awards were granted this year. The goals of this synergistic grant proposal are
to develop mathematical and biological tools to investigate the relationship between mammographic density, the
number of stromal cells in the breast, and the ability of stromal and epithelial cells to grow (proliferate). These
tools will help us to better understand breast cancer risk and whether women are responding to prevention.
 Under the supervision of Dr. Joseph Lo: Christy Shafer has been exploring quantitative breast tomosynthesis and
has shown encouraging preliminary results which will be presented at SPIE 2008. Vorakarn Chanyavanich has been
working on a collaboration with the FDA to compare and combine CAD algorithms for mammography. Swatee Singh
has passed her preliminary examination and continues her work in collaboration with Dr Tourassi to investigate an
information theory approach for mass detection in breast tomosynthesis; For a given new patient, similar 2D or 3D
image data are retrieved from our growing database of tomosynthesis human subjects and are used to generate a
diagnosis for that new patient. Shawn Mendonca is staying on for a year as a Research Technician II to continue work
on Bayesian Image Estimation in breast tomosynthesis and chest radiography after having graduated with a BSE in
biomedical engineering in spring 2007.
 A new joint project between DAI Labs and Radiation Oncology in optimization of IMRT for prostate cancer has
been launched and involves Vorakarn Chanyavanich, Drs. Lo, Tourassi of DAI Labs, and Shiva Das, PhD and Robert Lee,
MD of Radiation Oncology.
 In collaboration with Dr. Wesley Bolch of the University of Florida (UF) and Dr. Mike Stabin of Vanderbilt University
(VU), Dr. Segars has been working on developing new tools for assessment of radiation doses in therapy. These
include patient-specific realistic anatomic models to be used in clinical assessment of radiation dose and realistic
animal models to be used in preclinical trials. This was the subject of an NIH ROI grant proposal submitted in
November from UF and an SBIR proposal submitted in December from VU.
Research Updates (continued):
 Dr. Segars, Greg Sturgeon, Jason Grimes, and Shawn Mendonca continue development of a series of highly detailed
computational models of the male and female human anatomy at different ages for use in pediatric CT research.
For the adult models, work was done to develop enhanced models for the beating heart (Greg and Shawn) and for
the brain and its vasculature (Jason) based on dual source gated CT and high resolution MRI data, respectively.
 Drs. Segars, Dobbins, Lo, Tourassi, and Samei and Christina Li have begun a project to develop a series of detailed 3D
computational breast phantoms based on high-resolution CT data from Dr. John Boone from UC Davis for use in
breast imaging research. An NIH RO1 grant proposal was submitted on this subject in October. The models will be
capable of realistically simulating a wide range of anatomical variations in health and disease and have the added
flexibility to model different compression states of the breast for various imaging modalities.
 The interactive, information-theoretic CAD project led by Dr. Tourassi continues with the most recent studies
addressing the effect of image preprocessing (publication in Academic Radiology, pending) and the application of
advanced computational techniques for selecting the most informative cases when building knowledge databases. The
latter study will appear in Physics in Medicine and Biology in the near future and will be a featured article. In
collaboration with Dr. Lo, the information-theoretic CAD system is being applied to breast tomosynthesis data as well.
New results on an expanded database continue to be highly promising.
 Dr. Tourassi and Maciek Mazurowski have been investigating intelligent techniques to assess the patient-specific
reliability of decision support systems in breast cancer diagnosis. An R01 application on this topic is ready to be
submitted to NIH in February.
 Dr. Samei, Dr. Dobbins, Nicole Ranger and collaborators at KCARE, UK, have completed the evaluation of Effective
DQE (eDQE) for eight digital radiographic systems that represent a range of detector technologies. The evaluation is
being extended to a larger number of imaging systems with a specific aim to compare the technique against
conventional methods.
 Dr. Kapadia is continuing his research on the Neutron Stimulated Emission Computed Tomography (NSECT) project
to develop a clinical imaging device for detection of iron overload in the liver. Recent simulation experiments have
shown that NSECT has strong potential in detecting isolated regions of elevated iron concentration in a human liver
through tomographic scanning with clinically acceptable dose levels. These simulations are being developed further to
incorporate a portable neutron source and estimate the shielding requirements for a clinical scanner. Dr. Kapadia has
estab;osjed a collaboration with Dr. Warren Warren and Oak Ridge National Laboratories to develop NSECT using
ORNL's Spallation Neutron Source, which is a state-of-the-art research facility capable of producing neutron fluxes
several orders of magnitude higher than currently available sources at Duke. This collaboration project aims at
reducing patient scan times required for NSECT while maintaining clinically acceptable dose levels. Dr. Kapadia has
also set up a collaboration with the University of Wisconsin-Madison to develop neutron dosimetry models for NSECT in
collaboration with Dr. Paul DeLuca, who is one of the world leaders in fast neutron dosimetry. Dr. Kapadia is currently
applying for an NIH-R01 grant for feasibility testing of a clinical NSECT system through simulation development.
Awards and Honors
Paul Segars, PhD, received the IEEE Nuclear and Plasma Sciences Society’s 2007 Young Investigator Medical Imaging
Science Award “for contributions to the field of medical imaging through the development of innovative computerized
simulation tools widely utilized by the research community”. The award was presented in October 2007 at the IEEE
Nuclear Science Symposium / Medical Imaging Conference (NSS-MIC).
Ehsan Samei, PhD, was recognized by the American Association of Physicists in Medicine (AAPM) during the RSNA annual
conference, December 2007, for “Distinguished Service to Medical Physics”. He was also appointed to the AAPM
Science Council in January 2007.
In other notable contributions to the field of medical physics, in 2007 Drs. Jim Dobbins and Ehsan Samei launched the
Society of Directors of Academic Medical Physics Programs, an international society dedicated to enhancing graduate
medical physics education.
Christina Li and Swatee Singh were part of a team that won a Duke Start-Up Challenge: Executive Summary for
Healthcare, for their proposal for an implantable medical device which prevents focal epileptic seizures by delivering
targeted thermoelectric cooling to the brain on a micro-scale.
Focus on Research - Computer Aided Detection (CAD) and Image Processing
Dr. Qiang Li, PhD, joined the faculty of DAI Labs from the
University of Chicago in January 2008. Dr. Li is an internationally recognized expert in the evaluation of computer-aided
diagnostic (CAD) systems for evaluating lung cancer in chest
radiography, CT, and PET/CT, and the assessment of brain
tumor response in MRI.
Dr. Li developed a temporal subtraction technique using
an accurate image registration method, i.e., the elastic
matching method. Figure 1 shows a remarkably enhanced
lung cancer, seen as a dark shadow in the temporal subtraction image. Various observer studies conducted at multiple
institutions demonstrate that the temporal subtraction
method is a clinically useful technique for enhancing
lesions by removing rib structures in chest radiography.
Selective enhancement filtering for lung nodule detection is
a very important image processing technique for simultaneous enhancement of lung nodules and suppression of overlying
anatomical structures such as blood vessels. It can improve the
detection rate of lung nodules and can substantially reduce
the number of false positive detections in a CAD system.
Figure 2 shows an example of an enhanced image with
a nodule indicated by an arrow.
Previous
Current
Temporal
Subtraction
Fig. 1 Temporal Subtraction in Chest Radiography
using “elastic matching”
CAD schemes have the potential to assist radiologists to
improve the detection accuracy and efficiency for lung
nodules and for diffuse lung diseases in CT. The computerized detection schemes developed by Dr. Li and colleagues
have achieved high performance levels for the detection
of lung nodule and diffuse lung diseases. Figure 3 shows
a detected low-contrast lung nodule (arrow) and detected
areas (white ‘+’) with diffuse lung disease; the red line
indicates the reference standard delineated by radiologists.
Assessment of response to brain tumor therapy is an important emerging research field, in which accurate measurement
of tumor volume and growth rate plays a key role. The
accuracy of quantitative measurement of brain tumor further
relies on the accuracy of tumor segmentation in volumetric
MRI images. Spiral scanning is a new technique to transform
a volumetric 3D image into 2D space, and can thus considerably improve the accuracy and robustness of tumor segmentation algorithms. Figure 4 shows the original images and
segmentation results for a few slices of a brain tumor.
Original Images
Segmentation Results
Fig. 4 Tumor segmentation of volumetric MRI images for
assessment of response to therapy
Original
Enhanced
Fig. 2 Advanced Imaging Processing Techniques for
Improved Nodule Detection
Detected Nodule
Detected areas of diffuse lung
disease
Fig. 3 Advanced Imaging Processing Techniques for
Improved Nodule Detection
Focus on Research - Individualized Medical Decision Support
Computerized medical decision support systems are becoming increasingly popular in Radiology, providing a second
opinion during the diagnostic interpretation of imaging studies. Existing decision support systems are globally optimized
for the general population of prospective patients. Typically, the radiologist is informed about the system’s expected
accuracy in terms of overall sensitivity and specificity. However, the system’s patient-specific accuracy is neither
assessed nor communicated to the radiologist at the time of interpretation. Thus, for each patient, the radiologist is
unsure how much weight to assign to the second opinion offered by the decision support system. Studies have indeed
confirmed that there is wide variability amongst radiologists in usage and confidence when using commercially available
decision support computer aids.
To address this limitation, Dr. Georgia Tourassi has
been developing robust computational techniques that
enhance existing computer aids with the ability
to assess accurately the reliability of every opinion
they offer based on a dynamically selected sample
of known patients similar to the one being evaluated
(see Figure).
Her research capitalizes on theoretical advances
in computational intelligence, data mining, and
multiobjective optimization to deliver individualized
medical decision support.
Although this research is currently pursued for a multimodality computer assisted diagnosis system in breast cancer
diagnosis, it is relevant to all decision support systems.
As medical imaging is constantly advancing, researchers will continue to develop computer aids to help radiologists in the
diagnostic interpretation of increasingly more complex, high-volume clinical image data. Dr. Tourassi’s research aims to
improve the human-computer information interface and help support the radiologists’ cognitive process when they
consider the opinions offered by the decision support system.
Focus on Research - Radiation Dose Reduction in Pediatric CT
There have been recent publicity and interest is reducing radiation dose
associated with CT, currently the No. 1 source of man-made radiation
exposure to the US population. The concern about dose is further underscored for the pediatric population. In collaboration with Dr. Donald
Frush and his medical students, Dr. Ehsan Samei and Xiang Li study the
tradeoff between radiation dose and image quality in pediatric CT,
specifically, the effect of dose reduction on lung nodule/liver lesion
conspicuities. They developed a technique for three-dimensional modeling of small lung nodules on multi-detector array CT images (Figure 1).
The technique was validated through a ROC observer study which
demonstrated that experienced pediatric radiologists could not distinguish
between simulated and real lung nodules. Using proprietary noise addition
software, they simulated CT images at systematically reduced tube current (dose)
levels (Figure 2). By combining simulated nodules and noise with normal clinical
CT images, the influence of dose reduction on lung nodule detection was
evaluated through a ROC observer study. Their study revealed no general statistically significant difference in diagnostic accuracy at three systematically
reduced dose levels down to 75% dose reduction (Figure 3), suggesting potential
dose saving for initial diagnosis and follow-up
evaluation of lung nodules for pediatric CT
patients. A larger scale study is currently under
way to determine threshold dose levels needed to
detect small lung nodules in pediatric patients of
different age groups. Patient dose is assessed via a
parallel study in which organ dose and effective
dose values are estimated based on patientspecific data using our validated Monte Carlo
radiation transport program. This work is
partially supported by GE Healthcare.
DAI Labs Publications in 2007
1.
Badea CT, Hedlund LW, De Lin M, Mackel JS, Samei E, Johnson GA. Tomographic digital subtraction angiography for lung
perfusion in rodents. Med Phys 34:1546-1555, 2007.
2.
Baydush AH, Catarious DM, Lo JY, Floyd CE Jr. Incorporation of a Laguerre-Gauss channelized Hotelling observer for falsepositive reduction in mammographic mass CAD system. J Digit Imaging 20:196-202, 2007.
3.
Bender JE, Kapadia AJ, Sharma AC, Tourassi GD, Harrawood BP, Floyd CE. Breast cancer detection using Neutron Stimulated
Emission Computed Tomography: prominent elements and dose requirements, Med Phys 34:3866-3871, 2007.
4.
Chawla A, Samei E, Saunders RS. Abbey C, Delong DM, Effect of dose reduction on the detection of mammographic lesions: A
mathematical observer model analysis, Med Phys 34:3385-3398, 2007.
5.
Chawla A, Samei E. Ambient illumination revisited: A new adaptation-based approach for optimizing medical imaging reading
environments, Med Phys 34:81-90, 2007.
6.
Chawla A, Boyce S, Samei E, Design of a new multi-projection imaging system for chest radiography, Proc. IEEE NSS M13-M205:
2996-2999, 2007.
7.
Chawla A, Samei E, Abbey C, A mathematical model approach toward combining information from multiple image projections of
the same patient, Proc. SPIE Medical Imaging 6510:65101K1-11, 2007.
8.
Chawla A, Pollard B, Samei E, Hashimoto N, Effect of increased ambient lighting on detectability: a psychophysical study, Proc.
SPIE Medical Imaging 6516:6516171-12, 2007.
9.
Chen Y, Lo JY, Ranger NT, Samei E, Dobbins JT III. Methodology of NEQ (f) analysis for optimization and comparison of digital
breast tomosynthesis acquisition techniques and reconstruction algorithms, Proc. SPIE 6510:6510I1-9, 2007.
10.
Chen Y, Lo JY, Dobbins JT III. Importance of point-by-point back-projection (BP) correction for isocentric motions in digital
breast tomosynthesis: relevance to morphology of structures such as microcalcifications. Med Phys 34:3885-3892, 2007.
11.
Chen Y, Lo JY, Dobbins JT III. A comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) relevance to morphology of microcalcifications for isocentric motion in Digital Breast Tomosynthesis (DBT). Proc IEEE
Bioinformatics and Biomedical Engineering Conference - Boston, Massachusetts, 2007.
12.
Eltonsy NH, Tourassi GD, Elmaghraby AS. Contribution of Haar wavelets and MPEG-7 textural features for false positive reduction
in a CAD system for the detection of masses in mammograms. Proc SPIE Medical Imaging 6514:651404-1, 2007.
13.
Eltonsy NH, Tourassi GD, Elmaghraby AS. Morphologic concentric layer analysis for the detection of masses in screening
mammograms. IEEE Transactions in Medical Imaging 26:880-889, 2007.
14.
Eltonsy NH, Elmaghraby AS, Tourassi GD. Bilateral breast volume asymmetry in screening mammograms as a potential marker of
breast cancer: Preliminary experience. Proc 14th IEEE International Conference on Image Processing - San Antonio, Texas, 2007.
15.
Fetterly KA, Blume HR, Flynn MJ, Samei E. Introduction to Grayscale Calibration and Related Aspects of Medical Imaging Grade
Liquid Crystal Displays. J. Digit. Imaging, 2007. (online publication ahead of print)
16.
Floyd CE, Sharma AC, Bender JE, Kapadia AJ, Xia JQ, Harrawood BP, Tourassi GD, Lo JY, Kiser MR, Crowell AS, Pedroni RS,
Macri RA, Tajima S, Howell CR, Neutron Stimulated Emission Computed Tomography: Background Corrections, Nuclear Instruments
and Methods in Physics Research Section B 254:329-336, 2007.
17.
Fung GSK, Segars WP, Geschwind JFH, Tsui BMW, Taguchi K. Effect of Respiratory Motion on Abdominal C-Arm CT Angiography
Using the 4D NCAT Phantom. Proc 2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
18.
Habas PA, Zurada JM,Elmaghraby AS, Tourassi GD. Particle swarm optimization of neural network CAD systems with clinically
relevant objectives. Proc SPIE Medical Imaging 6514:65140M-1, 2007.
19.
Habas PA, Eltonsy NH, Elmaghraby AS, Zurada J, Tourassi GD. Reliability analysis of CAD decisions. Med Phys 34:763-772, 2007.
20.
Jerebko A, Quan Y, Merlet N, Ratner E, Singh S, Lo JY, Krishnan A. Feasibility study of breast tomosynthesis CAD system. Proc
SPIE Medical Imaging 6514:6514141-8, 2007.
21.
Jesneck JL, Lo JY, Baker JA. Breast mass lesions: computer-aided diagnosis models with mammographic and sonographic
descriptors. Radiology 244:390-398, 2007.
22.
Johnson JP, Lo JY, MertelmeierT, Nafziger JS, Timberg P, Samei E. Visual image quality metrics for breast tomosynthesis. Proc
SPIE 6515:65150P1-10, 2007.
23.
Kapadia AJ, Harrawood BP, Tourassi GD. A Geant4 Simulation for Iron Overload Detection using NSECT, Proc IEEE NSS-MIC Honolulu, Hawaii, 2007.
24.
Kinahan PE, Alessio AM, Segars WP, MacDonald L, Busch J, Kohlmyer S. Quantitative Evaluation of Respiratory Gated Whole-Body
PET/CT Imaging Incorporating Respiration Variability. Proc 2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
25.
Lee TS, Segars WP, Tsui BMW. The development and application of a realistic simulation dataset for simultaneous cardiac and
respirator gated ECT/CT. Proc 2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
26.
Li X, Samei E, Yoshizumi TT, Nguyen G, Daigle L, Colsher JG, Frush DP. Experimental benchmarking of a Monte Carlo dose
simulation code for pediatric CT. Proc. SPIE Medical Imaging 6510:65102A1-10, 2007. This paper received a Cum Laude award at
the SPIE Medical Imaging Symposium.
27.
Li CM, Dobbins JT III. Methodology for determining dose reduction for chest tomosynthesis. Proc. SPIE Medical Imaging
6510:65102D1-10, 2007.
28.
Mazurowski MA, Habas PA, Zurada JM, Tourassi GD. Impact of low class prevalence on the performance evaluation of neural
network-based classifiers: experimental study in the context of computer-assisted medical diagnosis. Proc 2007 International
Joint Conference on Neural Networks (IJCNN) - Orlando, Florida, 2007.
DAI Labs Publications in 2007 (continued #2)
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
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49.
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53.
54.
55.
56.
Mazurowski MA, Habas PA, Zurada JM, Tourassi GD. Case-base optimization for a computer-assisted breast cancer detection
system: an evolutionary approach. Proc 2007 Int Joint Conference on Neural Networks (IJCNN) - Orlando, Florida, 2007.
McKinley RL, Tornai MP, Floyd CE, Samei E. Contrast-detail comparison of computed mammotomography and digital
mammography. Proc SPIE Medical Imaging 6510:65101D1-10, 2007.
Peppler WW, Hong W, Whiting BR, Flynn MJ, Samei E. Validation of software for QC assessment of MTF and NPS. Proc SPIE
Medical Imaging 6510:65104F1-7, 2007.
Ranger NT, Samei E, Dobbins JT III, Ravin CE. Assessment of Detective Quantum Efficiency: Intercomparison of a Recently
Introduced International Standard with Prior Methods. Radiology 243:785-795, 2007.
Ruschin M, Timberg P, Båth M, Hemdal B, Svahn T, Saunders RS, Samei E, Andersson I, Mattsson S, Chakraborty DP, Tingberg A.
Dose dependence of mass and microcalcification detection in digital mammography: Free response human observer studies, Med
Phys 34:400-407, 2007.
Samei E, Saunders RS Jr, Baker JA, Delong DM, Digital mammography: effects of reduced radiation dose on diagnostic
performance, Radiology 243:396-404, 2007.
Samei E, Poolla A, Ulissey MJ, Lewin JM. Digital mammography: comparative performance of color LCD and monochrome CRT
displays. Acad Radiol 14:539-546, 2007.
Samei E, Stebbins SA, Dobbins JT III, McAdams HP, Lo JY. Multiprojection correlation imaging for improved detection of
coronary nodules. Am J Roentgenol 188:1239-1245, 2007.
Saunders RS, Jr, Samei E, Majdi-Nasab N, Lo JY. Initial human subject results for breast bi-plane correlation imaging technique,
Proc. SPIE 6514:6514231-7, 2007.
Saunders RS, Jr, Baker JA, Delong DM, Johnson JP, Samei E. Does image quality matter? Impact of resolution and noise on
mammographic task performance, Med Phys 34:3971-3981, 2007.
Segars WP, Tsui BMW. Enhanced 4D Heart Model based on High Resolution Dual Source Gated Cardiac CT Images. Proceedings of
the 2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
Segars WP, Mori S, Chen GTY, Tsui BMW. Modeling Respiratory Motion Variations in the 4D NCAT Phantom. Conference Record of
the Medical Imaging Conference and Nuclear Science Symposium - Honolulu, Hawaii, 2007.
Segars WP, Sandberg J, Li X, Samei E, Jones R, Frush D, Hollingsworth C, Tsui BMW. Transformable Computational Phantom for
Optimization of X-Ray CT Imaging Protocols. Proceedings of the 2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
Sharma AC, Harawood BP, Bender JE, Tourassi GD, Kapadia AJ. Neutron-stimulated emission computed tomography: a Monte
Carlo simulation approach. Phys Med Biol 52:6117-6131, 2007.
Sharma AC, Tourassi GD, Kapadia AJ, Harrawood BP, Crowell AS, Kiser MR, Howell CR, Floyd CE. Design and Development of a
High-Energy Gamma Camera for use with NSECT Imaging: Feasibility for Breast Imaging. IEEE Transactions on Nuclear Science
54:1498-1505, 2007.
Sharma, AC, Kapadia, AJ, Harrawood, BP, Tourassi, GD. Optimization of a Rotating Modulation Collimator for NSECT Imaging.
Proceedings of the 2007 IEEE NSS-MIC. Honolulu, HI, Nov 2007.
Sharma AC, Tourassi GD, Kapadia AJ, Crowell AS, Kiser MR, Hutcheson A, Harrawood BP, Howell CR, Floyd CE. Elemental
Spectrum of a Mouse Obtained via Neutron Stimulation. Proc SPIE Medical Imaging, 6510:65100K1-11, 2007.
Singh S, Tourassi GD, Lo JY. Breast mass detection in tomosynthesis projection images using information-theoretic similarity
measures. Proc SPIE Medical Imaging 6514:6514151-8, 2007.
Smyczynski MS, Gifford HC, Lehovich A, McNamara JE, Segars WP, Tsui BMW, King MA. Impact of Respiratory Motion on the
Detection of Small Pulmonary Nodules in SPECT Imaging. Proceedings of the 2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
Taguchi K, Sun Z, Segars WP, Fishman EK, Tsui BMW. Image-domain motion compensated time resolved 4D cardiac CT. Proc SPIE
Medical Imaging Conference, 2007.
Taguchi K, Zhang M, Frey EC, Xu J, Segars WP, Tsui BMW. Image-domain material decomposition using photon-counting CT.
Conference Record of the SPIE Medical Imaging 6510:651008-1, 2007.
Tang J, Lee TS, Segars WP, Tsui BMW. Detecting Cardiac Motion Defects from Simulated Gated SPECT Images. Proceedings of the
2007 IEEE NSS-MIC - Honolulu, Hawaii, 2007.
Tourassi GD, Harrawood B, Singh S, Lo JY, Floyd CE Jr. Evaluation of information-theoretic similarity measures for contentbased retrieval and detection of masses in mammograms. Med Phys 34:140-150, 2007.
Tourassi GD, Harrawood B, Singh S, Lo JY. Information-theoretic CAD system in mammography: Entropy-based indexing for
computational efficiency and robust performance. Med Phys 34:3193-3204, 2007.
Tourassi GD, Bilska-Wolak, Habas PA, Floyd CD Jr. Incorporation of a multi-scale texture-based approach to mutual information
matching for improved knowledge-based detection of masses in screening mammograms. Proc SPIE Medical Imaging 6514:6514031, 2007.
Tourassi GD, Bilska-Wolak, Habas PA, Floyd CE Jr. Cross-digitizer robustness of a knowledge-based CAD system for mass
detection in screening mammograms. Proc SPIE Medical Imaging 6514:651404-1, 2007.
Tourassi GD, Jesneck JL, Mazurowski PA, Habas PA. Stacked generalization in computer-assisted decision systems: Empirical
comparison of data-handling schemes. Proc 2007 Int Joint Conference on Neural Networks (IJCNN) - Orlando, Florida, 2007.
Xia JQ, Tourassi GD, Lo JY, Floyd CE Jr. On the development of a Gaussian noise model for scatter compensation. Proc SPIE
Medical Imaging 6510:65102M1-10, 2007.
Arrivals/Departures
Alumni News
Ying (Ada) Chen , PhD, successfully defended her PhD in summer 2007 and
joined the Biomedical Engineering Graduate Program at Southern Illinois
University as Assistant Professor of Electrical and Computer Engineering.
Jonathan Jesneck, PhD won the IEEE Academic
Service Award for his help in organizing the 7th IEEE
International Conference on Bioinformatics and
Bioengineering (BIBE07), where he chaired the
Proteomics Track and served as Poster Chair.
Jason Grimes, BS, MS, Research Assistant to Dr. Paul Segars, joined DAI Labs
in July, 2007 to develop a detailed computation model of the brain including
vasculature, for the purposes of modeling blood flow in health and disease.
Jonathan Jesneck, PhD, successfully defended his PhD in Bio-Engineering
and his MS in Statistics in the spring of 2007 and accepted a post-doctoral
position as a Computational Biology Fellow in the Cancer Program at the
Broad Insitute of Harvard University and the Massachusetts Institute of
Technology and in the Department of Pediatric Oncology at the Dana-Farber
Cancer Institute.
Anuj Kapadia, PhD, successfully defending his PhD in August, 2007 and
accepted a post-doctoral position at DAI Labs to continue his NSECT research.
Qiang Li, PhD, Associate Professor of Radiology, joined the DAI Labs faculty
01/03 (See Profile pg. 1 and Focus on Research, pg. 4). Dr. Li joins DAI Labs
from the University of Chicago, strengthening and expanding our existing CAD
research programme.
Mia Markey, PhD has received notification of a pending
promotion (effective Sept. 1st, 2008) to Associate
Professor with tenure at the University of Texas at
Austin.
Nariman Majdi Nasab, PhD recently joined Fujifilm
Medical Systems to work on CAD research applications.
Jessie Xia, PhD and her husband are pleased to
announce the arrival of baby Stephanie.
Faces of DAI Labs
Amy Sharma, PhD, successfully defended her PhD in the fall of 2007 and has
accepted a post-doctoral position in DAI Labs working with Dr. Tourassi.
Greg Sturgeon, BSE, MSE, Research Assistant to Dr. Paul Segars joined DAI
Labs in August, 2007 to develop a series of anatomical computational
phantoms for the pediatric through adult populations.
Jiahui Wang, PhD, joined DAI Labs on Jan 7, 2008 from the University of
Chicago, to continue his work as a post-doc with Dr. Qiang Li.
Jessie Xia, PhD, defended her PhD in the summer of 2007 and accepted a
post-doctoral position at Duke University in The National Institute of
Statistical Sciences and The Statistical and Applied Mathematical Science
Institute.
Other News
Dr. Paul Segars and his wife are pleased
to announce a new arrival. Baby Mathew
Scott Segars was born on Dec. 30th, 2007.
Both mother and child are doing well.
Swattee Singh passed her preliminary
examination and recently became engaged.
Congratulations and best of luck!
Duke Advanced Imaging Laboratories (DAI Labs)
Department of Radiology, Duke University Medical Center
2424 Erwin Road, Suite 302
Durham, NC 27705
Tel 919-684-1440, FAX 919-684-1492
URL: dailabs.duhs.duke.edu
From top left corner:
J Lo, Q Li, J Dobbins, E Samei, G Tourassi, P Segars
B Harrawood, J Baker, C. Ravin, P McAdams, N Ranger, B Britt
J Grimes, A Sharma, R Saunders, J. Wang, A. Kapadia, G Sturgeon
X Li, C Li, S Singh, A Chawla, X Li, S Boyce, C Shafer,
R Ike, V Chanyavanich, B Pollard, S Mendonca