The past two decades have witnessed revolutionary advances

in biomedical imaging modalities capable of providing

biological and physiological information from the cellular

scale to the organ level. Recent advances have also been

focused on cost-effective, noninvasive, portable, and molecularimaging

technologies for imaging at microscopic, mesoscopic,

and macroscopic levels. These technologies have significant

potential to advance biomedical research and clinical practice.

They can also provide a better understanding and monitoring

of physiological and functional disorders, which could lead to

mainstream diagnostic technologies of the future

Dhawan, Atam P.

Gurcan, Metin N.

Roysam, Badrinath

Wang, Lihong V.

Caltech Authors - Main

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 10, OCTOBER 2010 2551
Editorial
THE PAST two decades have witnessed revolutionary ad-vances in biomedical imaging modalities capable of pro-
viding biological and physiological information from the cel-
lular scale to the organ level. Recent advances have also been
focused on cost-effective, noninvasive, portable, and molecular-
imaging technologies for imaging at microscopic, mesoscopic,
and macroscopic levels. These technologies have significant
potential to advance biomedical research and clinical practice.
They can also provide a better understanding and monitoring
of physiological and functional disorders, which could lead to
mainstream diagnostic technologies of the future.
I. SCOPE OF THE SPECIAL ISSUE
This Special Issue addresses the emerging technologies in
multiparameter biomedical optical imaging and image analysis.
For this exciting area, this Special Issue invited contributions
in the general areas of multiparameter, multidimensional op-
tical microscopy, confocal microscopy, optical endoscopy and
spectroscopy, fluorescence imaging and tomography, diffuse re-
flectance and transillumination imaging, optical coherence to-
mography, multiphoton imaging and microscopy, photoacoustic
imaging and tomography, biophotonic imaging and tomography,
and image analysis (segmentation, registration, classification,
etc.). As a result of this call, we received a record number of
50 submissions that were reviewed by leading experts in their
respective areas. Among the many meritorious submissions,
18 were selected to highlight and represent the breakthrough
research at the leading edge of rapidly emerging technologies
and scientific research work with high impact and novelty.
It should also be noted that the guest editors also organized a
special session “Multi-parameter Biomedical Optical Imaging”
as part of 2010 IEEE International Symposium on Biomedical
Imaging: From Nano to Macro, 17 April 2010, Rotterdam, The
Netherlands, where several exciting papers on this topic were
presented.
II. SPECIAL ISSUE PAPERS
The papers in this Special Issue demonstrate some of the most
exciting developments in optical imaging and image analysis
from tissue to cellular and molecular levels.
Eleven papers dealing with multiparameter optical imaging
and image reconstruction methods for most promising modal-
ities such as optical coherence tomography (OCT), molecular
fluorescence tomography, multispectral transillumination imag-
ing, bioluminance tomography, and photoacoustic imaging are
presented first in this Special Issue. These papers demonstrate
novel optical microscopic and functional imaging methods
Digital Object Identifier 10.1109/TBME.2010.2072750
for important tissue characterization and potential diagnostic
applications.
Yao et al. present a simple method to numerically correct
optical-axis calculation in polarization-sensitive OCT. Through
experimental studies in tendon tissue, they demonstrate the ap-
plication of their method to mapping the 2-D optical axis distri-
butions in enface polarization-sensitive OCT images.
Yalavarthy et al. show that if a priori knowledge of the re-
fractive index for the segmented regions of tissue, or even an
approximated value, is used instead of assuming identical refrac-
tive index for all regions of tissue, then much accurate estimates
of optical properties can be obtained.
Tian et al. address the problem of over smoothing due to
Tikhonov regularization in fluorescence molecular tomography.
They utilize a third-order simplified spherical harmonics ap-
proximation to radiative transfer equation to model the photon
propagation within biological tissue.
D’Alessandro et al. present novel methods of recover-
ing depth-dependent measurements from transillumination im-
ages obtained through the Nevoscope, estimating the depth-
dependent point spread function, and ratiometric analysis for
the quantification of oxy- and deoxy-hemoglobin. The presented
methods can be used for reliable quantitative analysis of multi-
spectral Nevoscope images for early detection of angiogenesis
leading to early diagnosis of skin cancers.
Liu et al. address two issues to improve the quantitative
assessment of blood-oxygen saturation level: implementation
of a spectral normalization technique to eliminate the spec-
tral modulation induced by the wavelength-distance dependent
point spread function of OCTs and the reduction of the spectral
speckle noise due to the highly scattering blood. They assess the
effectiveness of their methods using common-path OCT system.
Wang et al. introduce a dual-modality imaging system by
integrating optical-resolution photoacoustic microscopy and
fluorescence confocal microscopy to provide optical absorp-
tion and fluorescence contrasts simultaneously. They demon-
strate simultaneous photoacoustic angiography and fluorescence
lymphangiography.
Tian et al. describe the analysis of quantitative reconstruction
deviation from peak wavelength shift of luminescent source
and the deviation of heterogeneous mouse model for biolumi-
nescence tomography. They discuss that the reconstruction re-
sults are significantly affected by the peak wavelength shift and
deviation of anatomical structure animal models, and the model
deviations exhibit much more influence than the wavelength
shift on the reconstruction results.
Yu et al. reformulate bioluminescence tomography as a least
absolute shrinkage and selection operator (LASSO) problem
with regularization, and propose a fast reconstruction algorithm
named as stage-wise fast LASSO (SwF-LASSO) is to solve
this problem. Through numerical simulations, they demonstrate
0018-9294/$26.00 © 2010 IEEE
2552 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 10, OCTOBER 2010
that their algorithm is not sensitive to measurement noise, can
achieve high computational efficiency, and accurately localize
source even without any permissible region constraint.
Khan et al. develop an algorithm to estimate a single-line
medial axis, the basis for computation of band profile rep-
resentative of intensity distribution over chromosomes. They
find their algorithm to be robust and capable of estimating a
satisfactory single-line medial axis and band profile to be a
good representative of intensity levels in different regions of
chromosomes.
Gibson et al. present an automated method for nonrigid reg-
istration of the optical nerve head surfaces extracted from seg-
mented 3-D OCT images. They illustrate construction of an
average optical nerve head shape across an illustrative dataset.
Jo et al. report early favorable results from an animal study
designed to measure the capacity of this approach for diagnos-
ing oral cancer in a hamster cheek pouch model of oral cancer
using their recently developed noninvasive imaging system in-
corporating OCT and fluorescence lifetime imaging to acquire
both sets of biomarkers.
The remaining set of papers addresses the issues of image
analysis for optical, radiological and histopathological image
analyses. Although radiological and optical image analyses have
attracted much of the attention in the past decades and enormous
strides have been made [1], there are several challenging prob-
lems still remaining. Histopathogical image analysis, on the
other hand, is truly an emerging area growing at an accelerated
pace, especially after the introduction of commercially available
whole-slide scanners. The size, complexity, scale, and biologi-
cal richness of these images constitute both the advantages and
challenges of this exciting field [2], [3].
Jung et al. present a novel watershed-based method for seg-
mentation of cervical and breast cell images by formulating the
segmentation of clustered nuclei as an optimization problem.
By using a priori knowledge with respect to the shape of nuclei,
they solve the optimization problem.
Lu et al. propose an automated retinal-layer-segmentation
technique for OCT images. Their experiments with four objects
demonstrate that their proposed technique segments the image
into five layers accurately.
Samsi et al. develop a follicle detection method from im-
munohistochemically stained slides of follicular lymphoma us-
ing texture and color information to mimic the process that a hu-
man expert might use to identify follicle regions. They compare
system-generated results with expert-generated ground truth and
show promising results.
Sertel et al. address computer-aided detection of centrob-
lasts for follicular lymphoma grading using adaptive likelihood-
based cell segmentation. The proposed system uses a unitone
conversion to obtain a single-channel image that has the max-
imum contrast and from the resulting image, a cell-likelihood
image is generated in an adaptive way that is robust to vari-
ations using the estimated parameters associated with hema-
toxylin stain concentration of pixels.
Cooper et al. illustrate the challenges associated with analyz-
ing and integrating large-scale image datasets with molecular
characterizations. They present their methodology for address-
ing these challenges in the context of a study on diffuse glioma
brain tumors, and present a motivating example for correlat-
ing nuclear morphometry with molecular characterization of
glioblastomas.
Tian et al. investigate an approach for automatic liver seg-
mentation from CT scans based on a statistical-shape model
integrated with an optimal-surface-detection strategy. They ap-
ply their method to MICCAI 2007 liver segmentation challenge
datasets.
Sadeghi Naini et al. propose a technique to enhance the
quality of intraoperative ultrasound images of a deflated lung
undergoing minimally invasive tumor-ablative procedure. The
proposed technique employs information of a deflated lung’s
computed tomography image constructed preoperatively in or-
der to enhance those of the intraoperative ultrasound images.
ACKNOWLEDGMENT
The guest editors would like to thank Prof. B. Wheeler, Editor-
in-Chief of TBME for his encouragement, advice, and continu-
ous support from the conceptualization of the special issue idea
and throughout the review process. They are also extremely
grateful to the reviewers who carefully reviewed the submis-
sions and provided extremely valuable and constructive cri-
tiques while providing all the feedback in a timely manner even
after unexpected delays in travel due to the volcanic eruption in
Iceland and during several proposal submission deadlines.
METIN N. GURCAN, Guest Editor
The Ohio State University
Columbus, OH 43210 USA
metin.gurcan@osumc.edu
BADRINATH ROYSAM, Guest Editor
Rensselaer Polytechnic Institute
Troy, NY 12180 USA
roysam@ecse.rpi.edu
ATAM P. DHAWAN, Guest Editor
New Jersey Institute of Technology
Newark, NJ 07102-1982 USA
dhawan@adm.njit.edu
LIHONG V. WANG, Guest Editor
Washington University in St. Louis
St. Louis, MO 63130 USA
hwang@biomed.wustl.edu
REFERENCES
[1] A. Dhawan, Medical Image Analysis. New York: Wiley-Interscience,
2003.
[2] M. Gurcan, L. Boucheron, A. Can, A. Madabhushi, N. Rajpoot, and
B. Yener, “Histopathological image analysis: A review,” IEEE Rev.
Biomed. Eng., vol. 2, pp. 147–171, 2009.
[3] Y. Al-Kofahi, W. Lassoued, W. Lee, and B. Roysam, “Improved automatic
detection & segmentation of cell nuclei in histopathology images,” IEEE
Trans. Bio-Med. Eng., vol. 57, no. 4, pp. 841–852, Apr. 2010.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 10, OCTOBER 2010 2553
Metin N. Gurcan (M’90–SM’05) received the B.Sc. and Ph.D. degrees in electrical and electron-
ics engineering from Bilkent University, Ankara, Turkey, and the M.Sc. degree in digital systems
engineering from the University of Manchester Institute of Science and Technology, Manchester,
U.K.
During 1996–1997, he was a Visiting Researcher at the University of Minnesota, Minneapolis.
From 1999 to 2001, he was a Postdoctoral Research Fellow and later a Research Investigator in
the Department of Radiology at the University of Michigan, Ann Arbor. Prior to joining the Ohio
State University, he worked as a Senior Researcher and Product Director at a high-tech company,
specializing in computer-aided detection and diagnosis of cancer from radiological images. He
is an Associate Professor at the Biomedical Informatics Department, The Ohio State University,
Columbus. He currently manages several image analysis related projects funded by the National
Cancer Institute, National Library of Medicine, American Cancer Society, Department of De-
fense and Children’s Neuroblastoma Cancer Foundation. He teaches tutorials IEEE International
Conference of Image Processing and International Conference on Acoustics, Speech, and Signal Processing, and is the Organizer
of and Lecturer at several meetings, workshops, special focus sessions at leading conferences in areas of image analysis.
Dr. Gurcan is a Senior Member of International Society for Optical Engineers and Radiological Society of North America.
He is the recipient of the British Foreign and Commonwealth Organization Award, Children’s Neuroblastoma Cancer Foundation
Young Investigator Award, and National Cancer Institute’s caBIG Embodying the Vision Award.
Badrinath Roysam (SM’89) received the B.Tech degree in electronics engineering from the
Indian Institute of Technology, Chennai, India, in 1984, and the M.S. and D.Sc. degrees from
Washington University, St. Louis, in 1987, and 1989, respectively.
He has been at the Rensselaer Polytechnic Institute, Troy, New York since 1989, where he is
currently a Professor in the Electrical, Computer, and Systems Engineering Department. He is
an Associate Director of the Center for Subsurface Sensing and Imaging Systems (CenSSIS)—a
multiuniversity National Science Foundation-sponsored engineering research center, and Codi-
rector of the Rensselaer Center for Open Source Software. He also holds an appointment in the
Biomedical Engineering Department. His current research interests include in the areas of multi-
dimensional biomedical image analysis with, biotechnology automation, optical instrumentation,
high-speed and real-time computing architectures, and parallel algorithms.
Dr. Roysam is a Senior Member of the Microscopy Society of America, International Society
for Analytical Cytology, Society for Neuroscience, and the Association for Research in Vision and
Ophthalmology. He is an Associate Editor for the IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING and IEEE TRANSACTIONS
ON INFORMATION TECHNOLOGY IN BIOMEDICINE.
2554 IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 57, NO. 10, OCTOBER 2010
0Atam P. Dhawan (M’79–SM’90–F’04) received the Bachelor’s and Master’s degrees from
the Indian Institute of Technology, Roorkee, India, and the Ph.D. degree from the University of
Manitoba, Manitoba, Canada, all in electrical engineering.
From 1985 to 2000, he held faculty positions in Electrical and Computer Engineering, and
Radiology Departments at several universities including University of Houston, University of
Cincinnati, University of Texas (Arlington), and University of Texas Medical Center (Dallas).
Currently, he is a Distinguished Professor of Electrical and Computer Engineering Department
with joint appointment in Biomedical Engineering at the New Jersey Institute of Technology,
Newark. His research work has been funded by National Institutes of Health (NIH), National
Science Foundation, and several industries. He is the author or coauthor of 200 research articles in
refereed journals, books, and conference proceedings. His current research interests are medical
imaging, multimodality medical image analysis, multigrid image reconstruction, wavelets, genetic
algorithms, neural networks, adaptive learning and pattern recognition.
Dr. Dhawan is the recipient of Commonwealth Fellowship during 1983–1985, Martin Epstein Award in 1984, NIH FIRST
Award in 1988, Sigma-Xi Young Investigator Award in 1992, University of Cincinnati Faculty Achievement Award in 1994,
the IEEE Engineering in Medicine and Biology Early Career Achievement Award in 1995, and University of Toledo Dorman
Distinguished Lecture Award in 1999. He is Senior Editor of the IEEE TRANSACTIONS OF BIOMEDICAL ENGINEERING (TBME) and
Editor-In-Charge of IEEE TBME Letters. He was the Chair of the “Emerging Technologies Committee” of the IEEE-Engineering
in Medicine and Biology Society from 1997 to 1999, and from 2009 to 2010. He was the Chair of the “New Frontiers in
Biomedical Engineering” Symposium at the World Congress 2000 on Medical Physics and Biomedical Engineering. He was the
Conference Chair of the IEEE 28th International Conference of Engineering in Medicine and Biology Society held from August
30 to September 3, 2006 in New York. He was an American Liaison and EMBS Representative in the Steering Committee of
International Symposium of Biomedical Imaging during 2009–2011. He has chaired numerous NIH review panels including the
NIH Biomedical Computing and Health Informatics Chartered Study Section.
Lihong V. Wang (M’96–SM’00–F’06) received the Ph.D. degree from Rice University, Houston,
Texas under the tutelage of Drs. Robert Curl, Richard Smalley, and Frank Tittel.
He is the holder of the Gene K. Beare Distinguished Professorship of Biomedical Engineering
at Washington University in St. Louis, St. Louis, MO, and directs the Optical Imaging Laboratory
and the Imaging Division. His Monte Carlo model of photon transport in scattering media has
been used worldwide. He is the author of one of the first textbooks in the field of biomedical optics.
He is the editor of the first comprehensive book on photoacoustic tomography. He is the author or
coauthor of more than 220 peer-reviewed journal articles and delivered more than 250 invited talks.
Dr. Wang is a Fellow of the AIMBE, OSA, and SPIE. He is the Editor-in-Chief of the
Journal of Biomedical Optics. He chairs the annual conference on Photons plus Ultrasound
and chaired the 2010 Gordon Conference on Lasers in Medicine and Biology and the 2010
OSA Topical Meeting on Biomedical Optics. He also chairs the International Biomedical Optics
Society. He is a Chartered Member on National Institutes of Health (NIH) study section. He
is the Founding Chair of the Scientific Advisory Boards for two companies commercializing photoacoustic tomography. He is
the recipient of NIH FIRST Award, National Science Foundation CAREER Award, and the 2010 Joseph W. Goodman Book
Writing Award. His laboratory invented or discovered frequency-swept ultrasound-modulated optical tomography, dark-field
confocal photoacoustic microscopy (PAM), optical-resolution PAM, photoacoustic Doppler sensing, photoacoustic reporter gene
imaging, focused scanning microwave-induced thermoacoustic tomography, exact reconstruction algorithms for photoacoustic
or thermoacoustic tomography, sonoluminescence tomography, Mueller-matrix optical coherence tomography, optical coherence
computed tomography, and oblique-incidence reflectometry.


Guest Editorial to the Special Letters Issue on Emerging Technologies in Multiparameter Biomedical Optical Imaging and Image Analysis

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Guest Editorial to the Special Letters Issue on Emerging Technologies in Multiparameter Biomedical Optical Imaging and Image Analysis

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