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Fig. 5 | Cancer Imaging

Fig. 5

From: Extracting value from total-body PET/CT image data - the emerging role of artificial intelligence

Fig. 5

Methodology for Normative Database Construction from PET/CT Data. Panel [A] depicts the sequential process for establishing a normative database derived from PET/CT data. The protocol initiates with a TB-PET examination, followed by patient stratification according to BMI, age, and gender. The subsequent phase involves deriving detailed organ segmentations from CT scans. These segmentations then guide diffeomorphic registrations to align subjects across diverse cohorts. The derived deformation fields from the CT alignments are applied to the corresponding PET data, culminating in a comprehensive normative database. Panels [B], [C], and [D] display representative maximum intensity projections PET images from the database, segmented by cohort characteristics. Panel [B] exemplifies a Japanese male cohort with a BMI range of 20.0-24.9, while Panels [C] and [D] represent European cohorts, male and female, respectively, both within the same BMI range. The noticeable radiotracer uptake observed in the right arm of the normative template image in panel [C] is an artifact attributable to the initial administration site of the radiopharmaceutical. Such localized hyperactivity represents a procedural remnant rather than pathological significance. Each panel provides the cohort’s demographic and sample size data, reflecting the database’s population diversity

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