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Articles 91 - 93 of 93
Full-Text Articles in Signal Processing
Applications Of Wavelet Transforms In Biomedical Optoacoustics, Zibiao Wei, Shujun Yang, Amin N. Dharamsi, Barbara Hargrave
Applications Of Wavelet Transforms In Biomedical Optoacoustics, Zibiao Wei, Shujun Yang, Amin N. Dharamsi, Barbara Hargrave
Biological Sciences Faculty Publications
We discuss the utility of wavelet transform methods in signal processing in general, and in particular, demonstrate the technique in optoacoustic applications. In several optoacoustic experiments with different samples, we have successfully enhanced the signal to noise ratios. Wavelet transforms optimize resolution by utilizing a tailored, variable time-window in different frequency regions. The technique's great advantage lies in the fact that the wavelet transform adds some redundancy to the original signal, and some desired features can be enhanced in the transformed space. In addition, proper choice of the basis set allows a sparse representation of the signal. Therefore, even when …
Three Dimensional Localization Of Lesions From Digitized Mammograms, Amy L. Magnus
Three Dimensional Localization Of Lesions From Digitized Mammograms, Amy L. Magnus
Theses and Dissertations
This thesis describes new algorithms to localize regions-of-interests (ROIs) three dimensionally from a pair of digitized mammograms. This work is intended to add a layer of sophistication to computer aided diagnosis by putting to use the fixed and measurable parameters of mammographic imaging. The fixed parameters are the source to film orientation and the podium-image distance. Measurable parameters are the rotation angle of the x-ray tube from the horizontal and the compression depth (the distance from compression paddle to contact podium distance) at the time of imaging. As an additional benefit, three dimensional localization algorithms alleviate the confusion radiologists may …
Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk
Computer Aided Detection Of Microcalcifications Utilizing Texture Analysis, Ronald C. Dauk
Theses and Dissertations
A comparative study of texture measures for the classification of breast tissue is presented. The texture features investigated include Angular Second Moments, Power Spectrum Analysis and a novel feature, Laws Energy Ratios. The texture study was accomplished as part of the development of a Model Based Vision (MBV) system for the automatic detection of microcalcifications. An overview of the Microcalcification Detection System is presented, which applies image differencing techniques, feature selection methods, and neural networks for locating microcalcification clusters in mammograms. The Power Spectrum Analysis feature set had the best overall performance with an 83% Probability of Detection and an …