Biomedical Signal Analysis: Contemporary Methods and Applications
Preface
If we knew what we were doing, it wouldn’t be called research, would it?
Albert Einstein (1879 –1955)
Our nation’s strongest information technology (IT) industry advances
are occurring in the life sciences, and it is believed that IT
will play an increasingly important role in information-based medicine.
Nowadays, the research and economic benefits are found at the intersection
of biosciences and information technology, while future years will
see a greater adoption of systems-oriented perspectives that will help
change the way we think about diseases, their diagnosis, and their treatment.
On the other hand, medical imaging is positioned to become a
substantial beneficiary of, and a main contributor to, the emerging field
of systems biology.
In this important context, innovative projects in the very broad field
of biomedical signal analysis are now taking place in medical imaging,
systems biology, and proteomics. Medical imaging and biomedical signal
analysis are today becoming one of the most important visualization and
interpretation methods in biology and medicine. The period since 2000
has witnessed a tremendous development of new, powerful instruments
for detecting, storing, transmitting, analyzing, and displaying images.
These instruments are greatly amplifying the ability of biochemists,
biologists, medical scientists, and physicians to see their objects of
study and to obtain quantitative measurements to support scientific
hypotheses and medical diagnoses.
An awareness of the power of computer-aided analytical techniques,
coupled with a continuing need to derive more information from medical
images, has led to a growing application of digital processing techniques
for the problems of medicine. The most challenging aspect herein lies
in the development of integrated systems for use in the clinical sector.
Design, implementation, and validation of complex medical systems require
not solely medical expertise but also a tight collaboration between
physicians and biologists, on the one hand, and engineers and physicists,
on the other.
The very recent years have proclaimed systems biology as the future
of biomedicine since it will combine theoretical and experimental approaches
to better understand some of the key aspects of human health.
The origins of many human diseases, such as cancer, diabetes, and cardiovascular
and neural disorders, are determined by the functioning and
malfunctioning of signaling components. Understanding how individual
components function within the context of an entire system under a
plentitude of situations is extremely important to elucidate the emergence
of pathophysiology as a result of interactions between aberrant
signaling pathways. This poses a new challenge to today’s pharmaceutical
industry, where both bioinformatics and systems biology/modeling
will play a crucial role. Bioinformatics enables the processing of the enormous
amount of data stemming from high-throughput screening methods
while modeling helps in predicting possible side effects, as well as
determining optimal dosages and treatment strategies. Both techniques
aid in a mechanistic understanding of both disease and drug action, and
will enable further progress in pharmaceutics by facilitating the transfer
from the “black-box” approach to drug discovery.
Download
http://s18.alxa.net/s18/srvs2/02/003...plications.rar
Preface
If we knew what we were doing, it wouldn’t be called research, would it?
Albert Einstein (1879 –1955)
Our nation’s strongest information technology (IT) industry advances
are occurring in the life sciences, and it is believed that IT
will play an increasingly important role in information-based medicine.
Nowadays, the research and economic benefits are found at the intersection
of biosciences and information technology, while future years will
see a greater adoption of systems-oriented perspectives that will help
change the way we think about diseases, their diagnosis, and their treatment.
On the other hand, medical imaging is positioned to become a
substantial beneficiary of, and a main contributor to, the emerging field
of systems biology.
In this important context, innovative projects in the very broad field
of biomedical signal analysis are now taking place in medical imaging,
systems biology, and proteomics. Medical imaging and biomedical signal
analysis are today becoming one of the most important visualization and
interpretation methods in biology and medicine. The period since 2000
has witnessed a tremendous development of new, powerful instruments
for detecting, storing, transmitting, analyzing, and displaying images.
These instruments are greatly amplifying the ability of biochemists,
biologists, medical scientists, and physicians to see their objects of
study and to obtain quantitative measurements to support scientific
hypotheses and medical diagnoses.
An awareness of the power of computer-aided analytical techniques,
coupled with a continuing need to derive more information from medical
images, has led to a growing application of digital processing techniques
for the problems of medicine. The most challenging aspect herein lies
in the development of integrated systems for use in the clinical sector.
Design, implementation, and validation of complex medical systems require
not solely medical expertise but also a tight collaboration between
physicians and biologists, on the one hand, and engineers and physicists,
on the other.
The very recent years have proclaimed systems biology as the future
of biomedicine since it will combine theoretical and experimental approaches
to better understand some of the key aspects of human health.
The origins of many human diseases, such as cancer, diabetes, and cardiovascular
and neural disorders, are determined by the functioning and
malfunctioning of signaling components. Understanding how individual
components function within the context of an entire system under a
plentitude of situations is extremely important to elucidate the emergence
of pathophysiology as a result of interactions between aberrant
signaling pathways. This poses a new challenge to today’s pharmaceutical
industry, where both bioinformatics and systems biology/modeling
will play a crucial role. Bioinformatics enables the processing of the enormous
amount of data stemming from high-throughput screening methods
while modeling helps in predicting possible side effects, as well as
determining optimal dosages and treatment strategies. Both techniques
aid in a mechanistic understanding of both disease and drug action, and
will enable further progress in pharmaceutics by facilitating the transfer
from the “black-box” approach to drug discovery.
Download
http://s18.alxa.net/s18/srvs2/02/003...plications.rar