To facilitate high level analysis of medical image data in research and clinical environments, a wrapper for the ITK toolkit is developed to allow ITK algorithms to be called in MATLAB. ITK is a powerful open-source toolkit implementing state-of-the-art algorithms in medical image processing and analysis. However, although ITK is rapidly gaining popularity, its user base is mostly restricted to technically savvy developers with expert knowledge of C++ and advanced programming concepts. MATLAB, on the other hand, is well-known for its easy-to-use, powerful prototyping capabilities that significantly improve productivity. Unfortunately, the 3D image processing capabilities of MATLAB are very limited and slow to execute. With the help of the wrapper we introduce in this paper, biomedical computing researchers familiar with MATLAB can harness the power of ITK while avoiding learning C++ and dealing with low-level programming issues. We strongly believe this functionality will be of considerable interest to the medical image computing community. In this paper we provide details about the design and usage of this interface in medical image filtering, segmentation, and registration.
KEYWORDS: Image registration, Image segmentation, Computed tomography, Finite element methods, 3D modeling, Magnetic resonance imaging, 3D image processing, Medical imaging, Medicine, Shape analysis
Recent advances in medicine conjecture that certain body fat may have mechanical function in addition to its classical role of energy storage. In particular we aim to analyze if the intra-articular fat pad of Hoffa is merely a space holder or if it changes shape to provide cushioning for the knee bones. Towards this goal, 3D CT images of real knees, as well as a skeletal knee model with fat simulating Hoffa's pad, were acquired in both extension and flexion. Image segmentation was performed to automatically extract the real and simulated fat regions from the extension and flexion images. Utilizing the segmentation results as binary masks, we performed automatic multi-resolution image registration of the fat pad between flexed and extended knee positions. The resulting displacement fields from flexion-extension registration are examined and used to calculate local fat volume changes thus providing insight into shape changes that may have a mechanical component.
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