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A Generic Approach to Organ Detection Using 3D Haar-Like Features

Jung, Florian and Kirschner, Matthias and Wesarg, Stefan (2013):
A Generic Approach to Organ Detection Using 3D Haar-Like Features.
In: Informatik aktuell, pp. 320-325, Springer, Berlin; Heidelberg; New York, Bildverarbeitung für die Medizin 2013, DOI: 10.1007/978-3-642-36480-8₅₆,
[Conference or Workshop Item]

Abstract

Automatic segmentation of medical images requires accurate detection of the desired organ as a first step. In contrast to application specific approaches, learning-based object detection algorithms are easily adaptable to new applications. We present a learning-based object detection approach based on the Viola-Jones algorithm. We propose several extensions to the original approach, including a new 3D feature type and a multi-organ detection scheme. The algorithm is used to detect six different organs in CT scans as well as the prostate in MRI data. Our evaluation shows that the algorithm provides fast and reliable detection results in all cases.

Item Type: Conference or Workshop Item
Erschienen: 2013
Creators: Jung, Florian and Kirschner, Matthias and Wesarg, Stefan
Title: A Generic Approach to Organ Detection Using 3D Haar-Like Features
Language: English
Abstract:

Automatic segmentation of medical images requires accurate detection of the desired organ as a first step. In contrast to application specific approaches, learning-based object detection algorithms are easily adaptable to new applications. We present a learning-based object detection approach based on the Viola-Jones algorithm. We propose several extensions to the original approach, including a new 3D feature type and a multi-organ detection scheme. The algorithm is used to detect six different organs in CT scans as well as the prostate in MRI data. Our evaluation shows that the algorithm provides fast and reliable detection results in all cases.

Series Name: Informatik aktuell
Publisher: Springer, Berlin; Heidelberg; New York
Uncontrolled Keywords: Business Field: Visual decision support, Research Area: Confluence of graphics and vision, Medical image processing, Medical imaging, Object detection
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Bildverarbeitung für die Medizin 2013
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1007/978-3-642-36480-8₅₆
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