Shape model training for concurrent localization of the left and right knee

Heike Ruppertshofen; Cristian Lorenz; Sarah Schmidt; Peter Beyerlein; Zein Salah; Georg Rose; Hauke Schramm

doi:10.1117/12.878090

14 March 2011 Shape model training for concurrent localization of the left and right knee

Heike Ruppertshofen, Cristian Lorenz, Sarah Schmidt, Peter Beyerlein, Zein Salah, Georg Rose, Hauke Schramm

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 796241 (2011) https://doi.org/10.1117/12.878090
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

An automatic algorithm for training of suitable models for the Generalized Hough Transform (GHT) is presented. The applied iterative approach learns the shape of the target object directly from training images and incorporates variability in pose and scale of the target object exhibited in the images. To make the model more robust and representative for the target object, an individual weight is estimated for each model point using a discriminative approach. These weights will be employed in the voting procedure of the GHT, increasing the impact of important points on the localization result. The proposed procedure is extended here with a new error measure and a revised point weight training to enable the generation of models representing several target objects. Common parts of the target objects will thereby obtain larger weights, while the model might also contain object specific model points, if necessary, to be representative for all targets. The method is applied here to the localization of knee joints in long-leg radiographs. A quantitative comparison of the new approach with the separate localization of right and left knee showed improved results concerning localization precision and performance.

Citation Download Citation

Heike Ruppertshofen, Cristian Lorenz, Sarah Schmidt, Peter Beyerlein, Zein Salah, Georg Rose, and Hauke Schramm "Shape model training for concurrent localization of the left and right knee", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796241 (14 March 2011); https://doi.org/10.1117/12.878090

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