8/8/2019 D027-tmi-ge-br1

1/2

IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 20, NO. 3, MARCH 2001 249

Book Review_____________________________________________________________________________

Handbook of Medical Imaging - Processing and Analysis Isaac

N. Bankman, Ed., 1st edition, 901 pages, Academic Press, New York,

2000 Reviewed by Ge. Wang

Medical imaging may be divided into two major components:image formation and image analysis. Medical image analysis becomes

increasingly important in matching the results of image acquisition

with specific domain requirements where the unprocessed original

images are complex, numerous, or contain subtle features. The

Handbook of Medical Imaging - Processing and Analysis, edited

by Isaac N. Bankman and a team of six section editors, provides an

overview of medical image analysis with tutorials on practical or

emerging methods. This handbook focuses on analysis of medical

images of all types, and consists of 53 chapters in six sections by

about 100 authors. Both established and cutting-edge algorithms are

grouped into six sections: enhancement, segmentation, quantification,

registration, visualization, and compression. Each section is briefly

introduced in a 2-3 page preface without references. The chapter

authors are active researchers and known experts from all over theworld. The editor, Isaac N. Bankman, is supervisor of the Imaging

and Laser Systems Section at the Johns Hopkins University Applied

Physics Laboratory (Baltimore, MD). He received the Ph.D. degree

in Biomedical Engineering from the Technion University of Israel,

Haifa, in 1985, and is active in the SPIE, OSA, and IEEE.

I. ENHANCEMENT

This section is the shortest among the six sections, consisting of four

chapters (66 pages). In this section, the authors discuss classic algo-

rithms and advanced adaptive filtering, multiscale nonlinear and hybrid

filtering methods. Among these methods, the multiscale wavelet-based

operators discussed in the last two chapters seem most powerful.

II. SEGMENTATION

This section contains nine chapters (146 pages). The fundamentals

are presented and representative approaches described, including fuzzy

clustering, neural networks, deformable models, hybrid segmentation,

followed by discussions on volumetric and partial volume segmenta-

tion. Chapters 810 deal with deformable model-based segmentation,

are well written, and are of particular interest to me.

III. QUANTIFICATION

This section consists of 12 chapters (210 pages). Texture analysis is

emphasized, followed by shape analysis, computational anatomy, mor-

phometry and computer aided diagnosis. These methods are applied in

neuroanatomy, musculoskeletal systems, mammography, and cardiacimaging. Image interpolation and re-sampling are covered.

IV. REGISTRATION

This section is the largest, consisting of 15 chapters (224 pages).

The central issue is handling of image distortions such as in magnetic

resonance imaging and positron emission tomography, and merging

different images for synergistic presentations. Feature extraction and

Manuscript received February 15, 2001.Publisher Item Identifier S 0278-0062(01)04722-X.

spatial transformation are exposed in detail. Within-modality, cross-

modality, multidimensional frameworks are all described. Validation

studies on registration accuracy are reported.

V. VISUALIZATION

This section includes five chapters (100 pages). The history and cur-

rent status of visualization and display are summarized. Commonly

used rendering methods are introduced. Virtual endoscopy is described.

My preference would be to enlarge this section, given its importance

and the plethora of novel post-processing techniques reported over the

past several years.

VI. COMPRESSION, STORAGE, AND COMMUNICATION

This last section contains eight chapters (136 pages). Industry stan-

dards for compression and digital image communication are defined

for medical image archive and retrieval, with an emphasis on picture

archiving and communication systems (PACS). Image quality evalu-ation is addressed in terms of diagnostic accuracy and statistics. The

wavelet compression scheme is emphasized. Finally, medical image

processing and analysis software packages are surveyed.

The handbook is valuable for researchers in image processing and

computer visionwho need an up-to-date review on medical image anal-

ysis. Generally speaking, the book does not prepare an interested engi-

neer from another subspecialty to fully understand key topics in med-

ical imaging. However, this handbook is an intermediary step that al-

lows the nonspecialist or student to learn the vocabulary and discover

some important applications in medical image analysis. This handbook

does not promise to provide a comprehensive survey and overview of

every topic. Take virtual colonoscopy for example. The corresponding

chapter was written by an outstanding researcher in the field, RonaldSummers of the National Institutes of Health (NIH). He places an em-

phasis on morphometric methods, which represents an area where he

has made unique and important contributions. However, other key is-

sues are not covered in detail, such as colon segmentation, center-

line tracking, computer aided diagnosis of polyps, interpretation of the

image results, design of clinical trials, specialized workstation strate-

gies, and the controversies in the field. It would be necessary to look

beyond the handbook for more specialized information, but this chapter

would prepare the reader to consult the literature with a much greater

chance for success. As another example, the chapter on shape transfor-

mations does not contain any equations. The handbook conspicuously

omits a detailed discussion of statistical shape modeling, which may

have been considered too esoteric or specialized to merit coverage in

detail, despite the strong interests of biologists and morphometriciansin this topic.

This handbook lacks an overview chapter that introduces medical

image analysis and explains why it makes sense to divide it into these

six categories. There is a preface, but an overview of the entire med-

ical image analysis field is so important to the reader that it merits a

chapter of its own. The handbook is not categorized according to the

application domain. In other words, we might divide medical imaging

according to modality or organ system or disease. This handbook does

not use any of these for its organization. If the reader is interested in

any specific modality, you would have to read each and everychapter to

determine whether the topic is relevant or not. The index is not helpful.

0278-0062/01$10.00 2001 IEEE

8/8/2019 D027-tmi-ge-br1

2/2

250 IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 20, NO. 3, MARCH 2001

The same problem exists for any given organ system or disease. You

cannot directly link them to specific chapters. Also, there are neither

CD-ROM demos nor a website associated with the book.

On the other hand, if you are trained in image processing, for ex-

ample, after introductory courses on these topics, you would find this

handbook to be a gold mine of information on how the fundamen-

tals that you just learned from the theoretical perspective are used in

medical applications. The organization of the handbook is natural for

anyone who has studied basic image processing and pattern recogni-

tion. This handbook does not prepare you to tackle specific problems,

however. It is an intermediate step between a general knowledge and

clinical research. This handbook can serve as a gateway to access the

relevant literature and acquire some of the essential vocabulary used in

medical imaging.

This handbook does not require great mathematical sophistication.

Any practicing engineer should be able to fully understand the hand-

book without additional references. It should also be clear that there

are large areas of medical imaging that are not included. These include

imaging physics, image reconstruction, noise and artifact reduction,

for example. With this handbook, the reader will be able to identify

the principal tools and methods of medical image analysis and many of

their applications. Given thedepth and diversity of themedical imaging

field, it is not realistic to expect that a single book would cover every

topic of importance. However, several more theoretical topics might

have been covered or explored in this book, such as image restoration,

signal/image separation, dynamic image analysis, and image modeling.

Some sophisticated mathematical approaches, either well developed

or newly emerged, are not included. As a positive consequence of this

omission, a large readership is assured for this book. However, the

power and the potential of more complex methods cannot be overes-

timated, such as hidden Markov field theory for image modeling, dif-

ferential equation techniques for image restoration, multiscale space

methods for image analysis, differential geometry for image visualiza-

tion, global pattern theory for image registration and recognition.

This handbook may be compared with similar recent compendia of

image processing methods and applications. The SPIE Handbook of

Medical Imaging1 and Image Processing Handbook2 are comparable

examples. The SPIE handbook is mathematically most sophisticated,

while the CRC handbook is most readable and technically most ef-

fectively presented for widest readership, since it treats topics beyond

medical imaging. The Bankman handbook lies between its peers. Any

multiauthored text is subject to quality variation. However, changes

from chapter to chapter in this handbook are greater than one would

expect in terms of mathematical and physical levels of presentation.

Generally speaking, the handbook is well integrated. The tables

and figures are effective. Each chapter can be read independently

with chapter-dependent prerequisites, which should be consistent to

the background of graduate students of biomedical, electrical and

computer engineering, and that of researchers in the medical imaging

field. If you cannot find the time to read the whole volume (and few

will be able to digest these 900 pages), you can just pick a chapter and

gain extensive information on current algorithms and recent advances

in medical image processing. As a handbook, there was no expectation

that it would be read in any particular order, and since the chapters

and sections are largely independent, this goal is well served. If you

are interested in any of the topics treated in the handbook, you can

enter at almost any point. The references cited are comprehensive and

up to date. Even well-established researchers will benefit, as the book

outlines the state-of-the-art and future directions, so it will serve well

in teaching these topics. The editors and the authors should be pleased

with the results of their work leading to an up-to-date compendium

of reviews and tutorials. This handbook is highly recommended for

engineers, physicists and practitioners who work or will enter the fast

growing field of medical image analysis.

1M. Sonka andJ. M. Fitzpatrick,Eds.Handbook of Medical ImagingII: Med-ical Image Processing and Analysis, (Bellingham, WA: SPIE Press, 2000, pp.200).

2J. C. Russ, Ed. The Image Processing Handbook, 3rd ed. (Boca Raton, FL:CRC Press, 1998, pp. 800).