Visual assessment of femoral osteopenia (the radiographic presentation of osteoporosis) is unreliable. Many of the short-comings of observer grading can be overcome by digital image analysis. Our group has developed algorithms to make automatic assessment of osteopenia from clinical radiographs. Texture Analysis Models (TA) commonly used in image analysis were investigated as measures of osteopenia. Unlike densitometric methods, TA characterizes properties of the structure of the image (ie, trabecular patterns). A group of women were analyzed whose subjects ranged from those at risk of osteoporosis (n = 24) to normal (n = 40). Using an IBM PC, frame-grabber, camera, and light-box, we appraised five statistical TA algorithms for assessment of the femoral neck in standard pelvic radiographs: (

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