Research Thrust R1Subsurface Sensing and Modeling

Research Thrust R1Subsurface Sensing and Modeling

Diverse Problems – Similar SolutionsDiverse Problems – Similar Solutions

Bahaa SalehCarey Rappaport

Bahaa SalehCarey Rappaport

A. OverviewB. Fundamental Sensor ResearchC. Computational ModelingD. Anticipated Results and Impact

A. OverviewB. Fundamental Sensor ResearchC. Computational ModelingD. Anticipated Results and Impact

A. OverviewA. Overview

SubsurfaceSensing and

Modeling

Validation Testbeds

Environmental-CivilApplications

Bio-MedicalApplications

Image and DataInformation

Management

Physics-BasedSignal Processing andImage Understanding

I–PLUS

R1R1R2R2

R3R3L1L1

L2L2

L3L3

Fundamental physics of SSISensor design and testingMathematical and computer modeling

R1 ScopeR1 Scope

EngineeredSystemEngineeredSystem

EnablingTechnologiesEnablingTechnologies

FundamentalScienceFundamentalScience

R1 GoalsR1 Goals

§ Test and validate new sensors § Incorporate modeling in testBEDs§ Test and validate new sensors § Incorporate modeling in testBEDs

§ Incorporate new sensors in Engineered System § Incorporate new modeling algorithms in

Software Resource Center

§ Incorporate new sensors in Engineered System § Incorporate new modeling algorithms in

Software Resource Center

L1L1

L2L2

L3L3

§ Develop better understanding of physics of SSI§ Develop new SSI concepts (nonlinear, dual wave)§ Develop new comput. modeling algorithms § Integrate phys & math modeling with inversion§ Develop a unified phys/math framework for SSI

§ Develop better understanding of physics of SSI§ Develop new SSI concepts (nonlinear, dual wave)§ Develop new comput. modeling algorithms § Integrate phys & math modeling with inversion§ Develop a unified phys/math framework for SSI

EE § Enhance engineering curriculumin photonics, acoustics, electromagnetics

§ Enhance engineering curriculumin photonics, acoustics, electromagnetics

I–PLUS

EngineeredSystemEngineeredSystem

EnablingTechnologiesEnablingTechnologies

FundamentalScienceFundamentalScience

EducationEducation

5

Diverse problems...Diverse problems...

Rough Surface

Inhomogeneous/Layered

MediumMedium

Absorption

Dispersion

Scattering

Diffusion

Clutter

Electro-magnetic

Optical/IR

X-rayAcoustic

CW Pulsed Modulated

CoherentMulti-

Spectral

Classical Quantum

Outside Inside Auxiliary

PartiallyCoherent

ObjectObject

Nonlinear Absorption

ScatteringNonlinear Scattering

DiffusivePhase Object

Depolarizing

Stationary Moving

Absorption Fluorescence

ProbeProbe

ObjectObject

SurfaceSurface

Detector(s)Detector(s)Probe(s)Probe(s)

MediumMedium

Need for a Unified FrameworkNeed for a Unified Framework

1 nm- 10 µm1 nm- 10 µm

Subcellular BiologySubcellular Biology Tissues & OrgansTissues & Organs

10 µm - 1 cm10 µm - 1 cm

10 cm - 1 km10 cm - 1 km

Optics Ultrasound

SonarRadar

1 cm - 100 m1 cm - 100 m

UndergroundDiagnosis

UndergroundDiagnosis

UnderwaterExplorationUnderwaterExploration

Broad Scale of Target Detail and WavelengthBroad Scale of Target Detail and Wavelength

Localized Probing & Mosaicing (LPM)Localized Probing & Mosaicing (LPM)Confocal Imaging

Pinhole

Focused Illumination

Focused Detection

Time-Resolved Imaging

Detector

Target

Time

Pulsed probe

Detectors

Target

Time

Diffusive

Ballistic

Time

Snake

Pulsed probe

Focused orPulsed Probe

Focused orGated Detector

Detector

Target

Mirrorx

x

Optical Coherence Tomography(sectioning)

Three Subsurface Imaging ModalitiesThree Subsurface Imaging Modalities

X-ray CAT Scanning & Diffraction Tomography

Detectors

Sources

Object

Crosswell Radar Tomography

Tra

nsm

itter

Arr

ayR

eceiver Array

InterwellRegion

Plume

Diffusive Wave Optical Tomography

Detector Array

Target

Source Array

Similar mathematical models

Similar mathematical models

Detectors

Sources

Object

Multiview Tomography (MVT)Multiview Tomography (MVT)

TNT Target Scattering in Smooth & Rough Sand

Ultra-Wideband GPR Resonance

Multi-wavelengthSource(s)

DetectorFilters

Fluorescence Microscopy

Wide BandProbe

Narrow BandDetectors

Satellite Hyperspectral Imaging

MultispectralDiscrimination (MSD)MultispectralDiscrimination (MSD)

§Density§Compressibility

Linear/nonlinear

§Density§Compressibility

Linear/nonlinear

§ Dielectric constant§ Conductivity§ Nuclear spin

§ Dielectric constant§ Conductivity§ Nuclear spin

§ Susceptibility§ Refractive index§ Absorption, § Birefringence§ Fluorescence

Linear/nonlinear

§ Susceptibility§ Refractive index§ Absorption, § Birefringence§ Fluorescence

Linear/nonlinear

AcousticAcoustic

ElectromagneticElectromagnetic

OpticalOptical

§ Physical properties (e.g., density, porosity, stiffness, ..)§Chemical composition §Metabolic information§ Extrinsic markers (dyes, chemical tags)

§ Physical properties (e.g., density, porosity, stiffness, ..)§Chemical composition §Metabolic information§ Extrinsic markers (dyes, chemical tags)

§ Absorption§ Geometry§ Absorption§ Geometry

X-RayX-Ray ElectricalElectrical§ Conductivity§ Impedance§ Conductivity§ Impedance

Need for Better Understanding of PhysicsNeed for Better Understanding of Physics

Barrier 1

Barrier 3

Barrier 4

Inadequate understanding of physics of SSI

Lack of robust, physics-based recognition & sensor fusion techniques

Lack of computationally efficient, realistic physical models

Lack of a unified framework for diverse sensing & imaging modalities

Barrier 8

R1 BarriersR1 Barriers

Lack of Optimal End to End Sensor Design MethodsLack of Optimal End to End Sensor Design MethodsBarrier 5

B. Fundamental Sensor Research

– Nonlinear Wave Imaging (R1a)– Dual-Wave Imaging (R1b )

B. Fundamental Sensor Research

– Nonlinear Wave Imaging (R1a)– Dual-Wave Imaging (R1b )

Research DirectionsResearch Directions

§ Greater contrast§ Greater SNR§ Finer axial resolution § Finer transverse resolution§ Deeper penetration§ Avoidance of obstructions & occlusions

§ Greater contrast§ Greater SNR§ Finer axial resolution § Finer transverse resolution§ Deeper penetration§ Avoidance of obstructions & occlusions

Improvement based on conventional state-of-the-art SSI techniques will only be incremental

Improvement based on conventional state-of-the-art SSI techniques will only be incremental

Nonlinear-Wave ImagingNonlinear-Wave Imaging

Dual-Wave ImagingDual-Wave Imaging

ObjectObject

SurfaceSurface

Detector(s)Detector(s)Probe(s)Probe(s)

MediumMedium

Nonlinear-Wave Imaging (Optical)Nonlinear-Wave Imaging (Optical)Two-Photon

Fluorescence Microscopy

Intense Laser

Detector

§ Reduced phototoxicity§ Enhanced resolution§ Reduced phototoxicity§ Enhanced resolution

Entangled-Photon Fluorescence Microscopy

Nonlinear Crystal

time

Photon Pairs

Fluorescence Photons

Laser

Weak Entangled-Photon Beams

§Understand the process of two-photon absorption for entangled light, including the effect of entanglement time and entanglement area §Determine axial and lateral resolutions for various configurations

§Understand the process of two-photon absorption for entangled light, including the effect of entanglement time and entanglement area §Determine axial and lateral resolutions for various configurations

Barrier 1 Inadequate understanding of physics of SSIInadequate understanding of physics of SSI

Entangled Photon Microscopy –A Quantum Inquisition Entangled Photon Microscopy –A Quantum Inquisition

Microscope lens

Mirror

Nonlinearcrystal

Laser beam

Beams of entangled photons

Mirror

Nervecell

From New Scientist, Vol. 164, 32-37 (1999)

Nonlinear-Wave Imaging (Acoustic)Nonlinear-Wave Imaging (Acoustic)

§ Nonlinear beam propagation & scattering from interfaces § Nonlinear bubble dynamics in Newtonian & viscoelastic media § Bioeffects (Cavitation, Heating)

§ Nonlinear beam propagation & scattering from interfaces § Nonlinear bubble dynamics in Newtonian & viscoelastic media § Bioeffects (Cavitation, Heating)

Short burst of high-intensitydiffraction-limited ultrasonicbeam at high frequency fo

Short burst of high-intensitydiffraction-limited ultrasonicbeam at high frequency fo

Backscattered wavereceived at 2 fo

Backscattered wavereceived at 2 fo

Nonlinear medium (tissue)or medium with nonlinear “agents,” e.g., bubbles

Nonlinear medium (tissue)or medium with nonlinear “agents,” e.g., bubbles

Image of in situ vein graft patch Note improved contrast & resolution

Image of in situ vein graft patch Note improved contrast & resolution

Barrier 1 Inadequate understanding of physics of SSIInadequate understanding of physics of SSI

LinearLinear

NonlinearNonlinear

Dual-Wave Imaging (Acousto-Photonic)Dual-Wave Imaging (Acousto-Photonic)

Optical Probes Detectors

Object

Conventional Diffusive Optical Tomography

Barrier 1 Inadequate understanding of physics of SSIInadequate understanding of physics of SSI

Barrier 3 Lack of robust, physics-based recognition & sensor fusion techniquesLack of robust, physics-based recognition & sensor fusion techniques

Applications: Soft-tissue imagingBreast tumor detectionPre-natal monitoringStroke differentiation

Addresses limited-view problem

Sound-assisted Diffusive Optical Tomography

Optical Probe Detector

Doppler-shifted Virtual probe

AcousticBeam

Object

Dual-Wave Imaging (Photo-Acoustic)Dual-Wave Imaging (Photo-Acoustic)

§ No ground contact is required§ Non-metallic objects & objects with no

dielectric contrast can be detected

§ No ground contact is required§ Non-metallic objects & objects with no

dielectric contrast can be detected

Field-test of laser-induced mine detection by NU & Laser Science, Inc,

at Univ. of Mississippi, Aug. 99

Field-test of laser-induced mine detection by NU & Laser Science, Inc,

at Univ. of Mississippi, Aug. 99

Barrier 1 Inadequate understanding of physics of SSIInadequate understanding of physics of SSI

Detectors

Laser

Sound wave

Photo-acousticsource

Target

Localized heating& expansion -->acoustic wave

R1a NonlinearImaging

R1a NonlinearImaging

R1b Dual WaveImaging

R1b Dual WaveImaging

Research TeamResearch Team

Ron Roy, BULeader

David Boas, MGH

Jon Stott, NU

Steve McKnight, NU

Bahaa Saleh, BU

Bahaa Saleh, BULeader

Ron Roy, BUCo-leader

Kristen Harris, BU

Malvin Teich, BU

Alan Pierce, BU

Alex Sergienko, BU

Robin Cleveland, BU

Chuck Dimarzio, NUCo-leader

C. Computational ModelingC. Computational Modeling

TestBEDExperiments

TestBEDExperiments

Inversion AlgorithmsInversion

Algorithms

SensorDesignSensorDesign

Computational Models

L2L2

PhysicalModels

PhysicalModels

VirtualLab

VirtualLab

R1R1

R2R2

L1, L2L1, L2

L3L3

Barrier 4Barrier 4 Lack of computationally efficient, realistic physical modelsLack of computationally efficient, realistic physical models

Why Is Computational Modeling Essential?Why Is Computational Modeling Essential?

R3R3

SoilBED experiments show need for modeling the distorting effects of realistic ground roughness on

Ground Penetrating Radar

SoilBED experiments show need for modeling the distorting effects of realistic ground roughness on

Ground Penetrating Radar

Surface Clutter Distorts Probing SignalsSurface Clutter Distorts Probing Signals

Computational Modeling (example)Computational Modeling (example)

The scattering signature of the buried target is highly distorted by the complex underground environment

The scattering signature of the buried target is highly distorted by the complex underground environment

FDTD Simulation of short-pulse GPR interaction with rough, dispersive ground and a buried plastic pipe.

FDTD Simulation of short-pulse GPR interaction with rough, dispersive ground and a buried plastic pipe.

Total Field, 2 GHz Mod. Gaussian Pulse

SoilSoil

AirAir

Computational Modeling (example)Computational Modeling (example)

By characterizing rough surface clutter, we establish strategies for best sensor placement

By characterizing rough surface clutter, we establish strategies for best sensor placement

Clutter onlyClutter onlyTarget and ClutterTarget and Clutter

Ground Response, No Target

SoilSoil

AirAirTotal Field, 2 GHz Mod. Gaussian Pulse

SoilSoil

AirAir

Computational Modeling (example)Computational Modeling (example)Total Field, 2 GHz Mod. Gaussian Pulse

SoilSoil

AirAirReceiver

Although we cannot observe clutter-only signal, we can use it to guide sensor placement

Although we cannot observe clutter-only signal, we can use it to guide sensor placement

Ground Response, No Target

SoilSoil

AirAir

Target Response

SoilSoil

AirAir

PlasticTarget

Feature

Priorities:ABCs for lossy media (1.5 yr) Auto. multiple time scales (2.5 yr)Geometry-specific gridding (3 yr)Non-linear field modeling (4 yr)Hybrid methods (5 yr) Statistical param. variation (5 yr)Real-time, 3D computation (10 yr)

Priorities:ABCs for lossy media (1.5 yr) Auto. multiple time scales (2.5 yr)Geometry-specific gridding (3 yr)Non-linear field modeling (4 yr)Hybrid methods (5 yr) Statistical param. variation (5 yr)Real-time, 3D computation (10 yr)

Air

Soil

Total Field, 2 GHz Mod. Gaussian Pulse

Gaussian rough surface specificationGaussian rough surface specification

Dispersive Media Modeling in Time

Dispersive Media Modeling in Time

PML Absorbing Boundary Conditions(ABC)

PML Absorbing Boundary Conditions(ABC)

Computational Modeling (Goals)Computational Modeling (Goals)

R1c ComputationalModeling

Carey Rappaport, NULeader

Paul Barbone, BUCo-Leader

Harold Raemer, NU

Sandra Cruz , UPRM

Magda El- Shenawee, NU

Ann Morgenthaler, NU

Research TeamResearch Team

D. Anticipated Results & ImpactD. Anticipated Results & Impact

R1 Integration With R2R1 Integration With R2

SubsurfaceSensing and

Modeling

Image and DataInformation

Management

Physics-BasedSignal Processing andImage UnderstandingR1R1

R2R2

R3R3

§ The strong coupling between R1 and R2 is a unique aspect of CenSSIS, which is expected to revolutionize SSI.

§ The strong coupling between R1 and R2 is a unique aspect of CenSSIS, which is expected to revolutionize SSI.

Level 1 (L1)FundamentalScience

Level 1 (L1)FundamentalScience

§ L1 research will result in new imaging techniques which will be validated in L2 testbeds § L1 research will address difficulties encountered in L2 testbeds and

L3 applications

§ L1 research will result in new imaging techniques which will be validated in L2 testbeds § L1 research will address difficulties encountered in L2 testbeds and

L3 applications

System Level (L1-L2-L3) IntegrationSystem Level (L1-L2-L3) Integration

SubsurfaceSensing and

Modeling

Validation Testbeds

Environmental-CivilApplications

Bio-MedicalApplications

Image and DataInformation

Management

Physics-BasedSignal Processing andImage Understanding

I–PLUS

R1R1R2R2

R3R3L1L1

L2L2

L3L3 EngineeredSystemEngineeredSystem

EnablingTechnologiesEnablingTechnologies

FundamentalScienceFundamentalScience

Yr 5Yr 4Yr 3Yr 2Yr 1

What Will Be Our Initial Program?What Will Be Our Initial Program?

New projectsNew projects

New System ConceptsNew System Concepts

New Sensing ConceptsNew Sensing Concepts⇒ BioBED⇒ BioBED

⇒ MedBED⇒ MedBED⇒ MedBED⇒ MedBED

⇒ SoilBED⇒ SoilBED

Entangled-photon microscopyEntangled-photon microscopy

Nonlinear ultrasonic imagingNonlinear ultrasonic imaging

Acousto-photonic imagingAcousto-photonic imaging

Photo-acousticPhoto-acoustic

Electrical Impedance TomographsElectrical Impedance Tomographs ⇒ MedBED⇒ MedBED

⇒ BioBED⇒ BioBEDQuadrature MicroscopeQuadrature Microscope

Subcellular TrackingSubcellular Tracking ⇒ BioBED⇒ BioBED

Civil-Underground Sensor FusionCivil-Underground Sensor Fusion ⇒ SoilBED⇒ SoilBED

Multi-Layer Hyperspectral ImagingMulti-Layer Hyperspectral Imaging ⇒ SeaBED⇒ SeaBED

Hi-Res Undersea VisualizationHi-Res Undersea Visualization ⇒ SeaBED⇒ SeaBED

Subretinal VisualizationSubretinal Visualization ⇒ MedBED⇒ MedBED

New courses in subsurface imaging & sensingNew courses in subsurface imaging & sensing

§Graduate course, Diagnostic Ultrasound Medical Imaging,Barbone & Szabo (Agilent), BU-AM503

§Graduate course, Microscopy (planned)§ Freshman course, Subsurface Sensing & Imaging, Saleh, BU-EK130

Modules added to existing engineering courses (Photonics, EM, Acoustics)

Modules added to existing engineering courses (Photonics, EM, Acoustics)

§Graduate course, Signals & Images (on Subretinal Imaging),Roysam, RPI-BMED4470

§Graduate course, EM Computational Modeling, Rappaport, NU-ECE3347§ Freshman course, Engineering Design/Subsurface Applications,

Rappaport, NU-GE1103

Experiments added to existing labs courses (Photonics, EM, Acoustics)

Experiments added to existing labs courses (Photonics, EM, Acoustics)

Student participation in relevant, applied, multi-disciplinary,theoretical & experimental research in sensing & imaging

Student participation in relevant, applied, multi-disciplinary,theoretical & experimental research in sensing & imaging

Impact on EducationImpact on Education

§ Testing of nonlinear & dual-wave sensors§ Incorporation of modeling in testBEDs§ Testing of nonlinear & dual-wave sensors§ Incorporation of modeling in testBEDs

L1L1

L2L2

L3L3

EE §An impact on engineering curriculum§An impact on engineering curriculum

Summary of Anticipated ResultsSummary of Anticipated Results

§ A unified phys/math framework for SSI§ Better understanding of physics of SSI§ New SSI concepts (nonlinear, dual wave)§ New & improved comput. modeling algorithms § Integration of phys/math modeling & inversion

§ A unified phys/math framework for SSI§ Better understanding of physics of SSI§ New SSI concepts (nonlinear, dual wave)§ New & improved comput. modeling algorithms § Integration of phys/math modeling & inversion

§ Incorporation of new sensors in I-PLUS § New modeling algorithms in

Software Resource Center

§ Incorporation of new sensors in I-PLUS § New modeling algorithms in

Software Resource Center

I–PLUS

EngineeredSystemEngineeredSystem

EnablingTechnologiesEnablingTechnologies

FundamentalScienceFundamentalScience

EducationEducation