This dissertation develops a public-domain approach for evaluating and selecting patient tissues to use for deriving densitometric computed tomography calibration (DCTC). This method enables the evaluation of patient computed tomography (CT) scans captured without a densitometric calibration phantom in the scan field of view. Unlike other methods for estimating density from CT scans, this method can be applied in the context of CTbased patient-specific finite element (CTPSFE) models and analyses. CTPSFE analyses have been shown useful in a variety of applications including identifying patients at risk of imminent femoral fragility fracture. This dissertation aims to demonstrate, verify, and validate an approach to selecting patient tissues to use as the basis for deriving a phantomless DCTC equation. My analysis shows the demonstrated phantomless method was comparable with current clinical and orthopaedic research gold standard phantombased calibration methods. The developed method shows promise as a public domain DCTC method capable of enabling further development of CTPSFE methods and broadening the clinical accessibility to quantitative CT analyses.