Automatic Skeletal Bone Age Assessment: State of the Art and Future Directions

Isaak Kavasidis, Carmelo Pino, and Edoardo Sicurezza

Keywords

skeletal bone age assessment, radiology, image processing, electronic noses, image processing, ROI processing, Orthodontics, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, x, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray, skeletal bone age assessment, radiology, image processing, ROI processing, Orthodontics, xray

Abstract

Determining the skeletal bone age is necessary in a variety of fields, ranging from pediatric radiology and endocrinology to crime investigation. Indeed, assessing the skeletal bone age is useful in situations like when developmental delays are present, in order to search for an organic cause, or when human age must be identified and no other evidence exists. One of the most used clinical methods to assess bone is the TW2 approach that, because of its modular nature, can be easily automated by image processing techniques. In the literature, many machine-vision based approaches have been proposed supporting the automation of the TW2 method; however there is still room for improvement since the achieved results are not completely satisfactory. This paper aims at reviewing these automatic methods, highlighting their peculiarities and providing future directions.

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