Statistical atlas based extrapolation of CT data

Gouthami Chintalapani; Ryan Murphy; Robert S. Armiger; Jyri Lepisto; Yoshito Otake; Nobuhiko Sugano; Russell H. Taylor; Mehran Armand

doi:10.1117/12.845570

27 February 2010 Statistical atlas based extrapolation of CT data

Gouthami Chintalapani, Ryan Murphy, Robert S. Armiger, Jyri Lepisto, Yoshito Otake, Nobuhiko Sugano, Russell H. Taylor, Mehran Armand

Author Affiliations +

Proceedings Volume 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling; 762539 (2010) https://doi.org/10.1117/12.845570
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

We present a framework to estimate the missing anatomical details from a partial CT scan with the help of statistical shape models. The motivating application is periacetabular osteotomy (PAO), a technique for treating developmental hip dysplasia, an abnormal condition of the hip socket that, if untreated, may lead to osteoarthritis. The common goals of PAO are to reduce pain, joint subluxation and improve contact pressure distribution by increasing the coverage of the femoral head by the hip socket. While current diagnosis and planning is based on radiological measurements, because of significant structural variations in dysplastic hips, a computer-assisted geometrical and biomechanical planning based on CT data is desirable to help the surgeon achieve optimal joint realignments. Most of the patients undergoing PAO are young females, hence it is usually desirable to minimize the radiation dose by scanning only the joint portion of the hip anatomy. These partial scans, however, do not provide enough information for biomechanical analysis due to missing iliac region. A statistical shape model of full pelvis anatomy is constructed from a database of CT scans. The partial volume is first aligned with the statistical atlas using an iterative affine registration, followed by a deformable registration step and the missing information is inferred from the atlas. The atlas inferences are further enhanced by the use of X-ray images of the patient, which are very common in an osteotomy procedure. The proposed method is validated with a leave-one-out analysis method. Osteotomy cuts are simulated and the effect of atlas predicted models on the actual procedure is evaluated.

Citation Download Citation

Gouthami Chintalapani, Ryan Murphy, Robert S. Armiger, Jyri Lepisto, Yoshito Otake, Nobuhiko Sugano, Russell H. Taylor, and Mehran Armand "Statistical atlas based extrapolation of CT data", Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 762539 (27 February 2010); https://doi.org/10.1117/12.845570

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