The assessment of skeletal bone age is an important step both in diagnostic and in therapeutic investigations of en-docrinological problems and growth disorders of children. Currently, there are two main approaches for skeletal bone age estimation that use X-Ray images: 1) the Greulich and Pyle (G&P) method and 2) the Tanner and Whitehouse (TW2 or TW3) methods. Although the G&P method is the most widely used for its simplicity, the TW2/TW3 method is the most accurate one, but it requires intensive training, especially for novice radiologists. The method is complex since it involves the simultaneous assessment of shapes and relative distances among several bones of the hand and with the further complication of the interaction between sex, age and race. In this paper we propose a computer-based system for assisting radiologists in the training with the Tan-ner&Whitehouse method; the system is based on an engine for automated assessment of skeletal bone age from X-Rays. In detail, after evaluating the user level, the system automatically proposes personalized training sessions by drawing from a wide repository of hand X-rays, and it suggests remedial sessions upon identification the features of the cases where the users demonstrated misconceptions. Finally, all the X-Rays that show combinations of features provenly difficult, are treated as teaching cases and are converted into Medical Imaging Resource Center (MIRC) format to ease their integration into more comprehensive digital educational resources.

A learning tool for assessing skeletal bone age in radiology

GIORDANO, Daniela;SPAMPINATO, CONCETTO;
2011

Abstract

The assessment of skeletal bone age is an important step both in diagnostic and in therapeutic investigations of en-docrinological problems and growth disorders of children. Currently, there are two main approaches for skeletal bone age estimation that use X-Ray images: 1) the Greulich and Pyle (G&P) method and 2) the Tanner and Whitehouse (TW2 or TW3) methods. Although the G&P method is the most widely used for its simplicity, the TW2/TW3 method is the most accurate one, but it requires intensive training, especially for novice radiologists. The method is complex since it involves the simultaneous assessment of shapes and relative distances among several bones of the hand and with the further complication of the interaction between sex, age and race. In this paper we propose a computer-based system for assisting radiologists in the training with the Tan-ner&Whitehouse method; the system is based on an engine for automated assessment of skeletal bone age from X-Rays. In detail, after evaluating the user level, the system automatically proposes personalized training sessions by drawing from a wide repository of hand X-rays, and it suggests remedial sessions upon identification the features of the cases where the users demonstrated misconceptions. Finally, all the X-Rays that show combinations of features provenly difficult, are treated as teaching cases and are converted into Medical Imaging Resource Center (MIRC) format to ease their integration into more comprehensive digital educational resources.
978-1-4577-1189-3
Learning systems; Automated assessment; Personalised learning
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/90350
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