Andrew D. A. Maidment

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Digital mammography systems allow manipulation of fine differences in image contrast by means of image processing algorithms. Different display algorithms have advantages and disadvantages for the specific tasks required in breast imaging-diagnosis and screening. Manual intensity windowing can produce digital mammograms very similar to standard screen-film(More)
We propose a multistep approach for representing and classifying tree-like structures in medical images. Tree-like structures are frequently encountered in biomedical contexts; examples are the bronchial system, the vascular topology, and the breast ductal network. We use tree encoding techniques, such as the depth-first string encoding and the PrUfer(More)
PURPOSE We present a novel algorithm for computer simulation of breast anatomy for generation of anthropomorphic software breast phantoms. A realistic breast simulation is necessary for preclinical validation of volumetric imaging modalities. METHODS The anthropomorphic software breast phantom simulates the skin, regions of adipose and fibroglandular(More)
The temporal comparison of mammograms is complex; a wide variety of factors can cause changes in image appearance. Mammogram registration is proposed as a method to reduce the effects of these changes and potentially to emphasize genuine alterations in breast tissue. Evaluation of such registration techniques is difficult since ground truth regarding breast(More)
Several types of breast carcinomas tend to spread along the surface of the ductal lumen. Spontaneous nipple discharge can be an early symptom of such cancer development that does not otherwise result in visible mammographic changes. An imaging procedure that can visualize such symptoms is galactography. We focus on characterizing the topology of the ductal(More)
RATIONALE AND OBJECTIVES Studies have demonstrated a relationship between mammographic parenchymal texture and breast cancer risk. Although promising, texture analysis in mammograms is limited by tissue superposition. Digital breast tomosynthesis (DBT) is a novel tomographic x-ray breast imaging modality that alleviates the effect of tissue superposition,(More)
We propose a multi-step approach for representing and classifying tree-like structures in medical images. Examples of such tree-like structures are encountered in the bronchial system, the vessel topology and the breast ductal network. We assume that the tree-like structures are already segmented. To avoid the tree isomorphism problem we obtain the(More)
PURPOSE The authors present an efficient method for generating anthropomorphic software breast phantoms with high spatial resolution. Employing the same region growing principles as in their previous algorithm for breast anatomy simulation, the present method has been optimized for computational complexity to allow for fast generation of the large number of(More)
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques and hybrid image statistics to perform branching node inference, using a support vector machine as a probabilistic inference framework. Then, we use local image statistics at(More)