Paper
10 March 2006 Toward fully automatic object detection and segmentation
Hauke Schramm, Olivier Ecabert, Jochen Peters, Vasanth Philomin, Juergen Weese
Author Affiliations +
Abstract
An automatic procedure for detecting and segmenting anatomical objects in 3-D images is necessary for achieving a high level of automation in many medical applications. Since today's segmentation techniques typically rely on user input for initialization, they do not allow for a fully automatic workflow. In this work, the generalized Hough transform is used for detecting anatomical objects with well defined shape in 3-D medical images. This well-known technique has frequently been used for object detection in 2-D images and is known to be robust and reliable. However, its computational and memory requirements are generally huge, especially in case of considering 3-D images and various free transformation parameters. Our approach limits the complexity of the generalized Hough transform to a reasonable amount by (1) using object prior knowledge during the preprocessing in order to suppress unlikely regions in the image, (2) restricting the flexibility of the applied transformation to only scaling and translation, and (3) using a simple shape model which does not cover any inter-individual shape variability. Despite these limitations, the approach is demonstrated to allow for a coarse 3-D delineation of the femur, vertebra and heart in a number of experiments. Additionally it is shown that the quality of the object localization is in nearly all cases sufficient to initialize a successful segmentation using shape constrained deformable models.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hauke Schramm, Olivier Ecabert, Jochen Peters, Vasanth Philomin, and Juergen Weese "Toward fully automatic object detection and segmentation", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614402 (10 March 2006); https://doi.org/10.1117/12.652060
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CITATIONS
Cited by 19 scholarly publications and 2 patents.
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KEYWORDS
Image segmentation

Heart

3D image processing

Hough transforms

Target detection

3D modeling

Computed tomography

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