Optimal Criteria for Functional Image Segmentation

Medical image segmentation is a very complicated process and the degree of complexity varies under different situations. Based on the results of a survey conducted among all centers performing emission tomographic studies and a series of international workshops to assess the goals and obstacles of data acquisition and analysis from emission tomography, Mazziotta et al. [15,16] proposed a series of optimal criteria to standardize and optimize PET data acquisition and analysis:

• Reproducible

• Independent of tracer employed

• Independent of instrument spatial resolution

• Independent of ancillary imaging techniques

• Minimizes subjectivity and investigator bias

• Fixed assumptions about normal anatomy not required

• Acceptable to subjects' level of tolerance

• Performs well in serial studies of the same patient and individual study of separate patients in a population

• Capable of evolving toward greater accuracy as information and instruments improve

• Reasonable in cost

• Equally applicable in both clinical and research settings

• Time efficient for both data acquisition and analysis

These criteria are not specific to the functional analysis of the brain, and they are equally applicable to other organs and imaging applications upon minor modifications, in spite of the fundamentally differences between imaging modalities.

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