Showing posts with label biomedical pattern recognition. Show all posts
Showing posts with label biomedical pattern recognition. Show all posts

6/14/2012

Biosignal and Medical Image Processing (Signal Processing and Communications) Review

Biosignal and Medical Image Processing (Signal Processing and Communications)
Average Reviews:

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This book assumes that you have both a prior knowledge of Matlab and of signal processing concepts. It spends the first three chapters going over measurement and transducer systems, basic signals and systems, and classical methods of spectral analysis. Even though these chapters are meant to be a quick review, there are some Matlab implementations of basic algorithms in each chapter. Chapter four introduces digital filters and shows Matlab implementations of both IIR and FIR filters. A special treat of chapter four is that some time is spent introducing the reader to the Matab signal processing toolkit. Now that the basics of digital filtering have been introduced, more advanced signal processing techniques are tackled. These include modern methods of spectral analysis and also time-frequency analysis using such methods as the Wigner-Ville distribution. Again, in all cases, the equations are concise, the prose is very accessible, and all concepts are demonstrated using Matlab programs. There is a separate chapter devoted to the wavelet transform and to its use in filter banks, denoising, and feature detection. Quite frankly, I found this chapter far more accessible than entire books that have been devoted to the subject, especially if you are interested in getting to the heart of the matter and using wavelets to perform a task. Two more chapters round out the section of the book on general signal processing techniques- one is about adaptive filters and another on principal component analysis. The final four chapters of the book concern themselves with image processing and Matlab, and the Matlab image processing toolkit in particular. You should already be familiar with the basic concepts behind image processing, and as with the signal processing portion of this book, the point is to have a single text with all of the relevant signal processing techniques briefly described along with Matlab code for the purpose of biosignal processing. However, even if you are not a biomedical engineer, and I am not, you should find this book helpful in the general sense of producing implementations of signal processing concepts. This book would also be helpful for biometric professionals since it goes into great detail on how to turn biological features into measurements that can be processed and compared.

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3/13/2012

Pattern Recognition in Medical Imaging Review

Pattern Recognition in Medical Imaging
Average Reviews:

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This is what I have always been looking for: A. Meyer-Baese presents an excellent book covering both a general introduction and a comprehensive survey on pattern recognition for biomedical purposes. I think the author provides a nice balance between theory and practice. The textbook can serve as an outstanding introduction of exceptional quality for everybody who wants to find precise, yet understandable discussions on how cutting-edge medical image analysis works, including methods for feature selection and extraction, wavelet analysis, neural networks and applications.
In summary, no matter whether you are a student or an expert interested in the field of biomedical pattern and image recognition: This book is what you need and a definite `must have'!


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Medical Imaging has become one of the most important visualization and interpretation methods in biology and medecine over the past decade. This time has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying medical images. This has led to a huge growth in the application of digital processing techniques for solving medical problems. The most challenging aspect of medical imaging lies in the development of integrated systems for the use of the clinical sector. Design, implementation, and validation of complex medical systems requires a tight interdisciplinary collaboration between physicians and engineers because poor image quality leads to problematic feature extraction, analysis, and recognition in medical application. Therefore, much of the research done today is geared towards improvement of imperfect image material. This important book by academic authority Anke Meyer-Baese compiles and organizes a complete range of proven and cutting-edge new methods, which are playing a leading role in the improvement of image quality, analysis and interpretation in modern medical imaging. These methods offer fresh tools of hope for physicians investigating a vast number of medical problems for which classical methods prove insufficient.Each chapter in Pattern Recognition for Medical Imaging provides a chapter summary and bibliographic remarks for in-depth study. Each presented classification approach is elucidated by a flow-diagram and highlighted with practical medical imaging applications. This is an essential tool for the serious student and professional working with Medical Imaging. *Essential tool for serious students and professionals working with Medical Imaging

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