Phase-Adaptive Superresolution of Mammographic Images Using Complex Wavelets

“…There are many methods of resolution enhancement, some of them are also called super resolution methods [26][27][28]. However, most of them introduce external information, noise and artifacts, in general coming from the averaging criteria of these methods, limiting the microcalcification identification.…”

Section: Super-resolution Srmentioning

confidence: 99%

MPGD for breast cancer prevention: a high resolution and low dose radiation medical imaging

Gutiérrez¹,

Cerquera²,

Mañana³

2012

J. Inst.

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Early detection of small calcifications in mammograms is considered the best preventive tool of breast cancer. However, existing digital mammography with relatively low radiation skin exposure has limited accessibility and insufficient spatial resolution for small calcification detection. Micro Pattern Gaseous Detectors (MPGD) and associated technologies, increasingly provide new information useful to generate images of microscopic structures and make more accessible cutting edge technology for medical imaging and many other applications. In this work we foresee and develop an application for the new information provided by a MPGD camera in the form of highly controlled images with high dynamical resolution. We present a new Super Detail Image (S-DI) that efficiently profits of this new information provided by the MPGD camera to obtain very high spatial resolution images. Therefore, the method presented in this work shows that the MPGD camera with SD-I, can produce mammograms with the necessary spatial resolution to detect microcalcifications. It would substantially increase efficiency and accessibility of screening mammography to highly improve breast cancer prevention.

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“…Robinson et al [2] used multi-frame image reconstruction to produce high-resolution mammograms beyond the native resolution of a digital image sensor by way of accurate sub-pixel registration of aliased images. Several other image enhancement techniques have been proposed for this problem [3], [4], [5], [6], [7], [8]; however, improvements have been modest.…”

Section: Introductionmentioning

confidence: 99%

Super-resolution of mammograms

Zheng

Fuentes

Leung

2010

2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

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High-quality mammography is the most effective technology presently available for breast cancer screening. High resolution mammograms usually lead to more accurate diagnoses; however, they require large doses of radiation, which may have harmful effects. In this paper, we present a method to synthesize high-resolution mammograms from low-resolution inputs, which offers the potential of allowing accurate diagnoses while minimizing risks to patients. Our algorithm combines statistical machine learning methods and stochastic search to learn the mapping from low-resolution to high-resolution mammograms using a large dataset of training image pairs. Experimental results show that the super-resolution algorithm can generate highquality, high-resolution breast mammograms from low-resolution input with no human intervention.

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Phase-Adaptive Superresolution of Mammographic Images Using Complex Wavelets

Cited by 10 publications

References 19 publications

Super‐resolution image reconstruction using molecular docking

Super‐resolution image reconstruction using molecular docking

MPGD for breast cancer prevention: a high resolution and low dose radiation medical imaging

Super-resolution of mammograms

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