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IEEE International Symposium on biomedical Imaging

作者： M. Rajchl J. Yuan E. Ukwatta P. M. Peters Biomedical Engineering Graduate Program University of Western Ontario London ONT Canada Robarts Research Institute Imaging Laboratories London ONT Canada

ISBN: (纸本)9781457718571

We present a novel and fast interactive approach to multi-modality cardiac image segmentation, which employs the linearly ordered surfaces as an additional constraint. We show using such a geometrical constraint helps to significantly reduce user interaction and improve the accuracy of segmentation results at the same time. We solve the proposed multiregion segmentation problem with the order constraints by means of convex optimization, resulting in a fast and reliable flow maximization approach which implicitly embeds the linear order prior without introducing extra computation load. In this regard, a new fully parallelized continuous max-flow algorithm is proposed and implemented using GPGPU to segment a 3D volume within one second. We demonstrate our results over pathological trans-esophageal echocardiogram, cardiac CT and delayed enhancement MRI data sets.

关键词： Image segmentation Optimization Accuracy Computed tomography Blood Magnetic resonance imaging Shape

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Quantification of Tc-99m sestamibi distribution in normal breast tissue using dedicated breast SPECT-CT

Quantification of Tc-99m sestamibi distribution in normal br...

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11th International Workshop on Breast Imaging, IWDM 2012

作者： Mann, Steve D. Perez, Kristy L. McCracken, Emily K. E. Shah, Jainil P. Choudhury, Kingshuk R. Wong, Terence Z. Tornai, Martin P. Medical Physics Graduate Program Duke University Durham NC United States Department of Radiology Duke University Medical Center Durham NC United States Duke University Medical School Durham NC United States Department of Biomedical Engineering Duke University Durham NC United States

ISBN: (纸本)9783642312700

The use of Tc-99m-Sestamibi in molecular breast imaging is common due to its preferential uptake in malignant tissue. However, quantification of the baseline uptake in normal, healthy breast tissue is not possible using planar-imaging devices. Using our dedicated breast SPECT-CT system, an IRB approved pilot study is underway to quantify mean activity in normal breast tissue, and to differentiate uptake between adipose and glandular tissues. A cohort of patients at normal breast cancer risk undergoing another diagnostic Sestamibi study was imaged using the breast SPECT-CT system. SPECT images were corrected and quantitatively reconstructed using previously developed methods, and registered with the CT images. The CT images were segmented, and the average activity concentration was measured for glandular, adipose, and total breast tissue. Results indicate no preferential uptake between tissues and low average uptake, which may be used to determine a universal threshold for cancer detection. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Tissue

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Automated Hemochromatosis Spectra Analysis Using Neutron Stimulated Emission Tomography

Automated Hemochromatosis Spectra Analysis Using Neutron Sti...

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IEEE Nuclear Science Symposium and Medical Imaging Conference

作者： Quetzalcoatl Magana Anuj Kapadia Greeshma Agasthya Stephen Balinskas Spectralysis LLC Laguna Hills Department of Radiology and the Medical Physics Graduate Program Duke University Department of Biomedical Engineering and the Ravin Advanced Imaging Laboratories Duke University

ISBN: (纸本)9781467320283

We identified and diagnosed hemochromatotic cases with an automatic technique based on peak recognition and chemometrics. Hemochromatosis is a disease characterized by an accumulation of iron in body organs. Neutron-stimulated emission computed tomography (NSECT) has demonstrated its ability to detect elevated iron concentrations in the liver through a non-invasive, low dose scan. Fast neutrons are used to generate gamma-ray emission from atomic nuclei in the liver, and the spectral energies of the emitted gamma photons are used to identify the elements of interest. The ability to analyze all gamma lines in the spectra, belonging either to an individual element or to different elements, significantly enhances the overall sensitivity, accuracy, and effectiveness of the diagnosis. We developed a novel peak-finding/peak-fitting algorithm, which rapidly processes all spectra collected on a large scale (i.e. all peaks within each spectrum in a set of spectra), and classifies the samples into healthy and diseased categories. The technique finds, deconvolves, and characterizes peaks based on their position, height, full width at half maximum (FWHM), and area, classifying the samples automatically with two methods, incriminant (novel) and discriminant analysis. We demonstrated that the algorithm classified a population of 64 healthy and 120 diseased simulated patients into healthy and hemochromatotic groups with clinically significant accuracy.

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Lineage structure of the human antibody repertoire in response to influenza vaccination

Lineage structure of the human antibody repertoire in respon...

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第五届中美生物医学工程暨海内外生物力学学术研讨会

作者： Ning Jiang Jiankui He Joshua A.Weinstein Lolita Penland Sanae Sasaki Xiao-Song He Patrick C.Wilson Harry B.Greenberg Mark M.Davis Daniel S.Fisher Stephen R.Quake Department of Biomedical Engineering the University of Texas at AustinAustinTXUSA Department of Bioengineering Stanford University School of MedicineStanfordCaliforniaUSA Biophysics Graduate Program Stanford UniversityStanfordCaliforniaUSA Department of Immunology and Microbiology Stanford University School of MedicineStanfordCaliforniaUSA VA Palo Alto Health Care System Palo AltoCaliforniaUSA Department of Medicine Stanford University School of MedicineStanfordCaliforniaUSA Department of Medicine University of Chicago Pritzker School of MedicineChicagoIllinoisUSA Howard Hughes Medical Institute Department of Applied Physics Stanford UniversityStanfordCaliforniaUSA Department of Biology Stanford UniversityStanfordCaliforniaUSA

The adaptive immune system produces a large and diverse set of antibodies,each with an individual evolutionary and clonal *** so called " antibody repertoire" protects each individual against insults such as infection and cancer,and responds to vaccination with B cell proliferation in response to the antigenic *** and antigen-specific FACSbased analysis have given us much insight on how the immune system generates the complex and diverse immune response required to protect the body from the wide variety of potential ***,these methods have not been sufficient to make global and unbiased

关键词： Lineage structure of the human antibody repertoire in response to influenza vaccination

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Identification and modeling of the electrohydraulic systems of the main gun of a main battle tank

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AIP Conference Proceedings 2012年第1期1493卷 207-214页

作者： Luiz C. A. Campos Luciano L. Menegaldo Defense Engineering Program Military Institute of Engineering Pça General Tibúrcio 80 22290-270 Rio de Janeiro Brazil Biomedical Engineering Program The Alberto Luiz Coimbra Institute for Graduate Studies and Research in Engineering Federal University of Rio de Janeiro Av. Horácio Macedo 2030 CT-Bloco H-338 Rio de Janeiro Brazil and Defense Engineering Brazil

The black-box mathematical models of the electrohydraulic systems responsible for driving the two degrees of freedom (elevation and azimuth) of the main gun of a main battle tank (MBT) were identified. Such systems respond to gunner's inputs while acquiring and tracking targets. Identification experiments were designed to collect simultaneous data from two inertial measurement units (IMU) installed at the gunner's handle (input) and at the center of rotation of the turret (output), for the identification of the azimuth system. For the elevation system, IMUs were installed at the gunner's handle (input) and at the breech of the gun (output). Linear accelerations and angular rates were collected for both input and output. Several black-box model architectures were investigated. As a result, nonlinear autoregressive with exogenous variables (NARX) second order model and nonlinear finite impulse response (NFIR) fourth order model, demonstrate to best fit the experimental data, with low computational costs. The derived models are being employed in a broader research, aiming to reproduce such systems in a laboratory virtual main gun simulator.

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Estimation of sleep onset latency based on the correlation between blood pressure and heart beat interval

Estimation of sleep onset latency based on the correlation b...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Da Woon Jung Gih Sung Chung Su Hwan Hwang Kwang Suk Park Interdisciplinary Program of Bioengineering Graduate School Seoul National University Seoul South Korea Department of Biomedical Engineering College of Medicine Seoul National University Seoul South Korea

Sleep onset latency (SOL) provides an objective assessment of sleepiness and it also clinically useful as a sleep deprivation diagnostic tool. In this study, we suggest a new approach to estimate SOL based on the correlation between blood pressure (BP) and heart beat interval (HBI). This approach facilitates less intrusive finding of SOL as compared with currently using polysomnographic method. We hypothesized that the arterial baroreflex, one kind of reflex mechanism to regulate BP, takes a role of maintaining sleep's toning-down effect on BP. At the time of transition from full wakefulness to sleep, the toning-down effect starts to drop the BP and the arterial baroreflex is activated to maintain lowered BP by leading to increase in HBI for the elevated BP. Consequently, there is a great contribution of arterial baroreflex to HBI control. With a quantitative evaluation of the contribution, we tried to estimate SOL. For six healthy subjects (27.5 ± 3.15 years), the mean absolute error (MAE) was 0.3 ± 0.42 minutes. We expect our method can be applicable to non-intrusive and automatic SOL estimation system by not using electroencephalogram (EEG) sensors.

关键词： Sleep Lead Medical diagnostic imaging Protocols Electrocardiography Position measurement Weight measurement

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31st Annual Meeting and Associated programs of the Society for Immunotherapy of Cancer (SITC 2016): part one: National Harbor, MD, USA. 9-13 November 2016

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J Immunother Cancer 2016年第SUPPL 1期4卷 1-1页

作者： Andreas Lundqvist Vincent van Hoef Xiaonan Zhang Erik Wennerberg Julie Lorent Kristina Witt Laia Masvidal Sanz Shuo Liang Shannon Murray Ola Larsson Rolf Kiessling Yumeng Mao John-William Sidhom Catherine A. Bessell Jonathan Havel Jonathan Schneck Timothy A. Chan Eliot Sachsenmeier David Woods Anders Berglund Rupal Ramakrishnan Andressa Sodre Jeffrey Weber Roberta Zappasodi Yanyun Li Jingjing Qi Philip Wong Cynthia Sirard Michael Postow Walter Newman Henry Koon Vamsidhar Velcheti Margaret K. Callahan Jedd D. Wolchok Taha Merghoub Lawrence G. Lum Minsig Choi Archana Thakur Abhinav Deol Gregory Dyson Anthony Shields Cara Haymaker Marc Uemura Ravi Murthy Marihella James Daqing Wang Julie Brevard Catherine Monaghan Suzanne Swann James Geib Mark Cornfeld Srinivas Chunduru Sudhir Agrawal Cassian Yee Jennifer Wargo Sapna P. Patel Rodabe Amaria Hussein Tawbi Isabella Glitza Scott Woodman Wen-Jen Hwu Michael A. Davies Patrick Hwu Willem W. Overwijk Chantale Bernatchez Adi Diab Erminia Massarelli Neil H. Segal Vincent Ribrag Ignacio Melero Tara C. Gangadhar Walter Urba Dirk Schadendorf Robert L. Ferris Roch Houot Franck Morschhauser Theodore Logan Jason J. Luke William Sharfman Fabrice Barlesi Patrick A. Ott Laura Mansi Shivaani Kummar Gilles Salles Cecilia Carpio Roland Meier Suba Krishnan Dan McDonald Matthew Maurer Xuemin Gu Jaclyn Neely Satyendra Suryawanshi Ronald Levy Nikhil Khushalani Jennifer Wu Jinyu Zhang Fahmin Basher Mark Rubinstein Mark Bucsek Guanxi Qiao Cameron MacDonald Bonnie Hylander Elizabeth Repasky Shilpak Chatterjee Anusara Daenthanasanmak Paramita Chakraborty Kyle Toth Megan Meek Elizabeth Garrett-Mayer Michael Nishimura Chrystal Paulos Craig Beeson Xuezhong Yu Shikhar Mehrotra Fei Zhao Kathy Evans Christine Xiao Alisha Holtzhausen Brent A. Hanks Nicole Scharping Ashley V. Menk Rebecca Moreci Ryan Whetstone Rebekah Dadey Simon Watkins Robert Ferris Greg M. Delgoffe Jonathan Peled Sean Devlin Anna Staffas Melissa Lumish Kori Porosnicu Rodriguez Katya Ahr Miguel Perales Sergio Giralt Ying Taur Eric Pam Karolinska Institutet Stockholm Stockholms Lan Sweden Weill Cornell Medical College New York NY USA Nova Southeastern University Cell Therapy Institute Fort Lauderdale FL USA Johns Hopkins University School of Medicine Baltimore MD USA Immunology Program Johns Hopkins University School of Medicine Columbia MD USA Memorial Sloan Kettering Cancer Center New York NY USA Johns Hopkins Medical Institute Baltimore MD USA University of Rochester Monrovia MD USA NYU Langone Medical Center New York NY USA H. Lee Moffitt Cancer Center Tampa FL USA Ludwig Collaborative Laboratory Memorial Sloan Kettering Cancer Center New York NY USA Immune Monitoring Core Facility Memorial Sloan Kettering Cancer Center New York NY USA Leap Therapeutics Cambridge MA USA Department of Medicine Memorial Sloan Kettering Cancer Center New York NY USA Case Western Reserve University Cleveland OH USA Cleveland Clinic Main Campus Cleveland OH USA University of Virginia Cancer Center Charlottesville VA USA Stony Brook University Medical Center Stony Brook NY USA Karmanos Cancer Institute Detroit MI USA University of Texas MD Anderson Cancer Center Houston TX USA Idera Pharmaceuticals Inc. Cambridge MA USA Institut Gustave Roussy Villejuif Ile-de-France France Center for Applied Medical Research (CIMA) University of Navarra Pamplona Navarra Spain University of Pennsylvania Philadelphia PA USA Earle A. Chiles Research Institute Providence Cancer Center Portland OR USA Universitätsklinikum Essen Essen Nordrhein-Westfalen Germany University of Pittsburgh Pittsburgh PA USA CHU Rennes Service Hématologie Clinique and INSERM 0203 Unité d’Investigation Clinique Rennes Bretagne France Centre Hospitalier Régional Universitaire de Lille Lille Nord-Pas-de-Calais France Simon Cancer Center Indiana University Indianapolis IN USA University of Chicago School of Medicine Chicago IL USA Johns Hopkins University School of Medicine Lutherville MD USA Multidisciplinary Oncology and Therapeuti

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A method to validate quantitative high-frequency power Doppler ultrasound with fluorescence in vivo video microscopy

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The Journal of the Acoustical Society of America 2013年第5_SUPPLEMENT期133卷 3540-3540页

作者： James C. Lacefield Stephen Z. Pinter Dae-Ro Kim M. Nicole Hague Ian C. MacDonald Ann F. Chambers Dept. of Med. Biophys. Western Univ. Thompson Engineering Bldg. Rm. 279 London ON N6A 5B9 Canadajlacefie@uwo.ca Biomedical Eng. Graduate Program Western Univ. London ON Canada Dept. of Med. Biophys. Western Univ. London ON Canada London Regional Cancer Program London ON Canada

Flow quantification with high-frequency power Doppler ultrasound can be performed using the wall-filter selection curve (WFSC) method [Elfarnawany et al., Ultrasound Med. Biol. 38, 1429–1439 (2012)]. The WFSC method plots color pixel density (CPD) as a function of wall filter cut-off velocity as a means of objectively selecting an operating point cut-off velocity. In this study, an in vivo video microscopy (IVVM) system was used to measure the size of small (140–400 μm diameter) mouse testicular vessels immediately after the vessels were imaged with 30 MHz power Doppler. The mouse remained on the same platform throughout ultrasound and IVVM imaging. Measurements in four image planes from three mice demonstrated that, similar to previously reported flow-phantom data, in vivo WFSCs exhibit distinct, sloped “characteristic intervals” at cut-off velocities where the CPD approaches the gold-standard IVVM estimate of vascular volume fraction. A wide range of operating point cut-off velocities (4.5 to 12 mm/s) was obtained, which indicates that use of a predetermined cut-off can produce substantial errors in cross-sectional studies that employ power Doppler to quantify vascularity. The WFSC method is a promising strategy for adapting the cut-off velocity to intersubject and longitudinal variations in blood flow during microvascular imaging experiments.

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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Application of a dynamic 4D anthropomorphic breast phantom in contrast-based imaging system optimization: Dual-energy or temporal subtraction?

Application of a dynamic 4D anthropomorphic breast phantom i...

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11th International Workshop on Breast Imaging, IWDM 2012

作者： Kiarashi, Nooshin Ghate, Sujata V. Lo, Joseph Y. Nolte, Loren W. Samei, Ehsan Carl E. Ravin Advanced Imaging Laboratories Duke University Medical Center Durham NC United States Department of Electrical and Computer Engineering Duke University Durham NC United States Department of Radiology Duke University Medical Center Durham NC United States Medical Physics Graduate Program Duke University Durham NC United States Department of Biomedical Engineering Duke University Durham NC United States Department of Physics Duke University Durham NC United States

ISBN: (纸本)9783642312700

We previously developed a dynamic 4D anthropomorphic breast phantom, which can be used to optimize contrast-based breast imaging systems, accounting for patient variability and contrast kinetics [1]. In this study we aim to compare the performance of contrast-enhanced mammographic and tomosynthesis imaging protocols followed by temporal subtraction and dual-energy subtraction, qualitatively and quantitatively across a couple of patient models. Signal-difference-to-noise ratio (SDNR) is measured for the six paradigms of contrast enhanced, temporally subtracted, and dual-energy subtracted mammography and tomosynthesis and compared. The results show how the performance is more dependent on the breast model in mammography than in tomosynthesis. Also, it is observed that dual-energy subtraction can be beneficial in mammography, whereas it is not advantageous in tomosynthesis. Lastly, the results suggest that temporal subtraction in general outperforms dual-energy subtraction. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Mammography

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