@article {226,
	title = {Phase-adaptive superresolution of mammographic images using complex wavelets},
	journal = {IEEE Transactions on Image Processing},
	volume = {18},
	year = {2010},
	pages = {1140 - 1146},
	abstract = {<p>This correspondence describes a new superresolution approach for enhancing the resolution of mammographic images using complex wavelet frequency information. This method allows regions of interest of a mammographic image to be viewed in enhanced resolution while reducing the patient exposure to radiation. The proposed method exploits the structural characteristics of breast tissues being imaged and produces higher resolution mammographic images with sufficient visual fidelity that fine image details can be discriminated more easily. In our approach, the superresolution problem is formulated as a constrained optimization problem using a third-order Markov prior model and adapts the priors based on the phase variations of the low-resolution mammographic images. Experimental results indicate the proposed method is more effective at preserving the visual information when compared with existing resolution enhancement methods.</p>
},
	keywords = {adaptive, mammography, phase, superresolution},
	author = {A Wong and J Scharcanski}
}
