Marginal Space Learning for Medical Image Analysis

Marginal Space Learning for Medical Image Analysis-1

Yefeng Zheng • Dorin Comaniciu

2014

Efficient Detection and Segmentation
of Anatomical Structures

Medical imaging is today an integrated part of the healthcare continuum, supporting early disease detection, diagnosis, therapy, monitoring, and follow-up. Images of the human body help in estimating the organ anatomy and function, reveal clues indicating the presence of disease, or help in guiding treatment and interventions. All these benefits are achieved by extracting and quantifying the medical image content, answering questions such as: “Which part of the 3D image represents the heart and what is the ejection fraction?”, “What is the volume of the liver”, “Which are the axillary lymph nodes with a diameter larger than 10 mm?”, “Is the artificial heart valve being positioned at the right location, with the right angulation?”

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