Milestone-Proposal:Shepp, 1972
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Docket #:2025-10
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To the proposer’s knowledge, is this achievement subject to litigation? No
Is the achievement you are proposing more than 25 years old? Yes
Is the achievement you are proposing within IEEE’s designated fields as defined by IEEE Bylaw I-104.11, namely: Engineering, Computer Sciences and Information Technology, Physical Sciences, Biological and Medical Sciences, Mathematics, Technical Communications, Education, Management, and Law and Policy. Yes
Did the achievement provide a meaningful benefit for humanity? Yes
Was it of at least regional importance? Yes
Has an IEEE Organizational Unit agreed to pay for the milestone plaque(s)? Yes
Has the IEEE Section(s) in which the plaque(s) will be located agreed to arrange the dedication ceremony? Yes
Has the IEEE Section in which the milestone is located agreed to take responsibility for the plaque after it is dedicated? Yes
Has the owner of the site agreed to have it designated as an IEEE Milestone? Yes
Year or range of years in which the achievement occurred:
1970-2000
Title of the proposed milestone:
Development of the Shepp Filtered Backprojection and Its Impact on Medical Imaging and Signal Reconstruction, 1970–2000
Plaque citation summarizing the achievement and its significance; if personal name(s) are included, such name(s) must follow the achievement itself in the citation wording: Text absolutely limited by plaque dimensions to 70 words; 60 is preferable for aesthetic reasons.
Lawrence Shepp’s Filtered Backprojection algorithm enabled accurate reconstruction of medical images from projection data, transforming computed tomography (CT) and enabling widespread diagnostic use. Developed at Bell Labs in the early 1970s, Shepp’s contributions extended to positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and probabilistic modeling for communication and biological systems, leaving a foundational legacy in signal and image reconstruction.
200-250 word abstract describing the significance of the technical achievement being proposed, the person(s) involved, historical context, humanitarian and social impact, as well as any possible controversies the advocate might need to review.
In 1974, Lawrence Shepp introduced the Filtered Backprojection (FBP) algorithm, a mathematically rigorous and computationally efficient method to reconstruct cross-sectional images from X-ray projections. This breakthrough directly enabled practical computed tomography (CT) and set a new standard in medical imaging. Shepp’s mathematical innovations did not stop at CT. He pioneered statistical frameworks for PET imaging, replacing geometric approaches with probabilistic models, and later contributed to high-speed fMRI techniques by introducing prolate wavelet-based sampling in 3D k-space, enabling the study of rapid neuronal dynamics via the initial negative BOLD response. Even in communication theory, Shepp advanced tractable probabilistic models for ultrawideband (UWB) systems subject to narrowband interference. His models utilized spatial Poisson point processes, advanced fading models, and Rake receivers to deliver closed-form BER expressions, combining mathematical elegance with engineering realism.
IEEE technical societies and technical councils within whose fields of interest the Milestone proposal resides.
Antennas and Propagation Society; Information Theory; Signal Processing; Image Processing; Nuclear & Plasma Sciences; Engineering in Medicine and Biology; Computational Intelligence; Communications Society; Vehicular Technology; Computer Society; Standards.
In what IEEE section(s) does it reside?
IEEE Organizational Unit(s) which have agreed to sponsor the Milestone:
IEEE Organizational Unit(s) paying for milestone plaque(s):
IEEE Organizational Unit(s) arranging the dedication ceremony:
IEEE section(s) monitoring the plaque(s):
Milestone proposer(s):
Proposer name: Katherine Grace August, PhD
Proposer email: Proposer's email masked to public
Proposer name: Thomas M Willis III, PhD
Proposer email: Proposer's email masked to public
Proposer name: Victor B Lawrence, PhD
Proposer email: Proposer's email masked to public
Please note: your email address and contact information will be masked on the website for privacy reasons. Only IEEE History Center Staff will be able to view the email address.
Street address(es) and GPS coordinates in decimal form of the intended milestone plaque site(s):
Describe briefly the intended site(s) of the milestone plaque(s). The intended site(s) must have a direct connection with the achievement (e.g. where developed, invented, tested, demonstrated, installed, or operated, etc.). A museum where a device or example of the technology is displayed, or the university where the inventor studied, are not, in themselves, sufficient connection for a milestone plaque.
Please give the details of the mounting, i.e. on the outside of the building, in the ground floor entrance hall, on a plinth on the grounds, etc. If visitors to the plaque site will need to go through security, or make an appointment, please give the contact information visitors will need.
Are the original buildings extant?
Details of the plaque mounting:
How is the site protected/secured, and in what ways is it accessible to the public?
Who is the present owner of the site(s)?
What is the historical significance of the work (its technological, scientific, or social importance)? If personal names are included in citation, include detailed support at the end of this section preceded by "Justification for Inclusion of Name(s)". (see section 6 of Milestone Guidelines)
Justification for Inclusion of Name: Lawrence A. Shepp The inclusion of Lawrence A. Shepp's name in the title of this IEEE Milestone is fully justified based on the following criteria, aligned with IEEE History Committee guidelines for named recognition:
1. Foundational Contribution to the Achievement Lawrence Shepp was the primary innovator and mathematical architect of the Filtered Backprojection (FBP) algorithm that revolutionized computed tomography (CT). His seminal 1974 paper with Benjamin Logan introduced a direct reconstruction method based on Fourier inversion of Radon transform data, replacing iterative, time-consuming, and less accurate techniques. This method became widely known as the Shepp Filtered Backprojection, establishing a named association that continues in scholarly and clinical use to this day.
Moreover, Shepp introduced the Shepp-Logan Phantom, a synthetic model that allowed exact computation of projection integrals for benchmarking CT algorithms. This model is still used worldwide to validate image reconstruction techniques and appears by name in academic software libraries (e.g., MATLAB: phantom()).
2. Widely Recognized by the Scientific and Engineering Communities Shepp's name is permanently linked to FBP and mathematical image reconstruction in both academic literature and clinical imaging systems:
The term “Shepp-Logan Filtered Backprojection” appears in textbooks, peer-reviewed publications, and imaging system documentation.
The Shepp-Logan Phantom is a universal standard in medical image reconstruction.
His contributions are cited across multiple disciplines: biomedical imaging, statistical signal processing, and applied mathematics.
3. Singular, Individual Recognition While some aspects of the original work involved collaborators (notably Logan), Shepp’s role in defining the mathematical framework, designing the phantom, and extending the work into PET and fMRI was singular. His continued leadership in tomographic imaging and statistical signal reconstruction spanned decades, making him the unifying figure across these transformative advances.
In PET, he introduced statistical maximum-likelihood methods with Yehuda Vardi, again replacing geometrically motivated reconstruction algorithms.
In fMRI, Shepp co-authored pioneering work on high-temporal-resolution imaging based on prolate wavelet theory and fast 3D k-space acquisition.
Across all these achievements, Lawrence Shepp provided the core mathematical insights, designed the computational techniques, and validated them with real-world impact.
In 1974, Lawrence Shepp introduced the Filtered Backprojection (FBP) algorithm, a mathematically rigorous and computationally efficient method to reconstruct cross-sectional images from X-ray projections. This breakthrough directly enabled practical computed tomography (CT) and set a new standard in medical imaging. Shepp’s mathematical innovations did not stop at CT. He pioneered statistical frameworks for PET imaging, replacing geometric approaches with probabilistic models, and later contributed to high-speed fMRI techniques by introducing prolate wavelet-based sampling in 3D k-space, enabling the study of rapid neuronal dynamics via the initial negative BOLD response. Even in communication theory, Shepp advanced tractable probabilistic models for ultrawideband (UWB) systems subject to narrowband interference. His models utilized spatial Poisson point processes, advanced fading models, and Rake receivers to deliver closed-form BER expressions, combining mathematical elegance with engineering realism.
What obstacles (technical, political, geographic) needed to be overcome?
Obstacles Overcome:
• Mathematical Intractability: The inversion of the Radon transform, required for CT, had to be implemented accurately and stably with finite, noisy data.
• Computational Constraints: 1970s computers necessitated efficient algorithms, which Shepp delivered via FBP and later PET iterative EM methods.
• Clinical Validation: Bridging theoretical math with real-world clinical systems required both simulated phantoms and collaborations with radiologists.
• Temporal-Resolution Gap in fMRI: Overcoming the slow temporal dynamics of traditional fMRI, Shepp developed sampling strategies based on wavelet theory.
• Wireless Complexity: Modeling spatially distributed interference with realistic fading in UWB communications required novel stochastic geometry and tractable approximations.
What features set this work apart from similar achievements?
Distinctive Features That Set Lawrence A. Shepp’s Work Apart: 1. Mathematically Rigorous Yet Practically Implementable Many early image reconstruction techniques were either:
Iterative and approximate (e.g., Hounsfield's method for CT), or
Theoretically precise but computationally infeasible.
Shepp’s Filtered Backprojection (FBP) was the first to:
Provide an exact inversion of the Radon transform using the Fourier Slice Theorem, and Translate it into a simple, fast, and stable algorithm implementable on 1970s computing hardware.
What sets it apart: Bridged pure mathematics and real-world clinical use—rare at the time.
2. Creation of a Universal Standard (Shepp-Logan Phantom) Shepp recognized the need for a quantifiable, reproducible standard to evaluate imaging algorithms. He designed the Shepp-Logan head phantom, which became:
The first widely accepted test image for CT performance evaluation, and A universal benchmark in both academic and commercial software systems (e.g., MATLAB’s phantom() function).
What sets it apart: Defined algorithmic evaluation methodology for decades of imaging science.
3. Transcended CT: Unified Theories Across Modalities Where most contributors focused on a single imaging modality, Shepp advanced foundational algorithms across CT, PET, and fMRI:
In PET, he introduced statistical estimation techniques (e.g., EM algorithm with Vardi), outperforming geometric models and incorporating the physical realities of radioactive emissions.
In fMRI, he pioneered high-temporal-resolution imaging using 3D k-space sampling every 100 ms—enabling detection of the initial negative BOLD response, closer to the true timing of neural activity.
What sets it apart: A unified mathematical approach applied across three distinct imaging modalities.
4. Integration of Statistical, Geometric, and Physical Models Shepp's work combined:
Fourier analysis and signal processing (FBP), Stochastic geometry and Poisson point processes (PET and wireless modeling), Functional analysis and wavelet theory (fMRI with prolate spheroidal functions), and Physical system constraints (e.g., k-space trajectory design, photon detection physics).
What sets it apart: Deep integration of diverse mathematical frameworks to model and solve real-world inverse problems.
5. Enduring Influence and Adoption The Shepp FBP algorithm remains in use today (as a baseline or hybrid component) in modern CT and SPECT scanners.
His phantom image is still the gold standard for algorithm testing.
His fMRI work prefigured current interest in ultra-fast cognitive imaging.
His UWB signal modeling with realistic channel effects and spatially distributed interference is still cited in wireless communications research.
What sets it apart: Unusually long-lasting impact across multiple decades and disciplines.
6. Personal Leadership and Vision Shepp did not merely contribute individual papers—he pioneered entire fields, led interdisciplinary collaborations (radiology, statistics, electrical engineering), and mentored a generation of researchers.
Despite the technological limitations of his time, his theoretical insights were always one step ahead, anticipating the needs of hardware and computation.
What sets it apart: Visionary foresight and leadership across academic, clinical, and engineering communities.
In summary, Lawrence Shepp’s work stands apart because it is comprehensive, cross-disciplinary, mathematically foundational, practically transformative, and enduring. Few contributions in engineering and applied mathematics can claim such breadth and depth of influence.
Why was the achievement successful and impactful?
Significance and Impact:
• Global Medical Practice: FBP became the default algorithm in CT scanners for decades, facilitating the global rollout of life-saving diagnostics.
• PET Imaging: Shepp's probabilistic EM-based models are still core to modern PET image reconstruction.
• fMRI Neuroscience: His fast fMRI techniques using prolate spheroidal wave functions helped reveal the rapid timing of brain region activation.
• Signal Processing Research: The Shepp-Logan Phantom remains a benchmark in algorithm testing and validation across imaging fields.
• Wireless Communications: His rigorous modeling of interference in UWB networks influenced design principles in modern mobile systems.
Supporting texts and citations to establish the dates, location, and importance of the achievement: Minimum of five (5), but as many as needed to support the milestone, such as patents, contemporary newspaper articles, journal articles, or chapters in scholarly books. 'Scholarly' is defined as peer-reviewed, with references, and published. You must supply the texts or excerpts themselves, not just the references. At least one of the references must be from a scholarly book or journal article. All supporting materials must be in English, or accompanied by an English translation.
Shepp, L.A., Logan, B.F. “The Fourier Reconstruction of a Head Section,” IEEE Transactions on Nuclear Science, Vol. 21, No. 3, 1974. Shepp, L.A., Vardi, Y. “Maximum Likelihood Reconstruction for Emission Tomography,” IEEE Trans. Medical Imaging, 1982. Lindquist, M., Zhang, C.-H., Glover, G., Shepp, L. “Rapid 3D fMRI of the Initial Negative BOLD Response,” Journal of Magnetic Resonance, 2008. Martin Lindquist, “From CT to fMRI: Larry Shepp’s Impact on Medical Imaging,” Johns Hopkins Biostatistics.
US Patents and Bell Labs Technical Memoranda on CT reconstruction methods. Adoption of FBP in commercial scanners by EMI, GE, Siemens, and others. Use of the Shepp-Logan Phantom in benchmark studies.
Herman, G.T., Image Reconstruction from Projections, Academic Press, 1980. National Academy of Sciences Biography of Lawrence Shepp. 5Interviews with contemporaries and documentation from Bell Labs’ archives.
Supporting materials (supported formats: GIF, JPEG, PNG, PDF, DOC): All supporting materials must be in English, or if not in English, accompanied by an English translation. You must supply the texts or excerpts themselves, not just the references. For documents that are copyright-encumbered, or which you do not have rights to post, email the documents themselves to ieee-history@ieee.org. Please see the Milestone Program Guidelines for more information.
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