Deep learning techniques have been extensively used in computerized pulmonary nodule
analysis in recent years. Many reported studies still utilized hybrid methods for diagnosis, in …

Wavelet analysis is a branch of applied mathematics that has produced a collection of tools
designed to process certain signals and images. This new book is devoted to describing …

Contrast enhancement of radiographies based on a multiscale decomposition of the images
recently has proven to be a far more versatile and efficient method than regular unsharp …

In view of the increasingly important role played by digital medical imaging in modern health
care and the consequent blow up in the amount of image data that have to be economically …

We develop a general algorithm for decomposition and compression of grayscale images.
The decomposition can be expressed as a functional relation between the original image …

Image-processing and pattern-recognition methodologies have found a variety of
applications in medical imaging and diagnostic radiology. Medical-image processing has …

In this paper we assess the relative merits of various types of wavelet functions for use in a
wide range of image compression scenarios. We have delineated different algorithmic …

In this paper we compute the maxisets of some denoising methods (estimators) for
multidimensional signals based on thresholding coefficients in hyperbolic wavelet bases …

Biomedical image compression plays an important role in the medical field. Mammograms
are medical images used in the early detection of breast cancer. Mammogram image …

This chapter provides new wavelet-based techniques for the automated detection and semi-
automated detection of certain early signs of cancer. It is concerned with the automated …