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Segmentation of Volume Data Based on 3D Lazy Snapping

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/39714

Title: Segmentation of Volume Data Based on 3D Lazy Snapping
Authors: Sun, Chia-Yang Browse this author
Ku, Cheng-Wei Browse this author
Issue Date: 4-Oct-2009
Publisher: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee
Journal Title: Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
Start Page: 391
End Page: 397
Abstract: The image segmentation techniques for medical image play important roles in computer-aided detection, analysis and measurement. Due to the computed tomography (CT) and the magnetic resonance imaging (MRI) technologies, the doctor can obtain volume images to visualize the structures of internal organ of human body. In this paper, we present a volume segmentation method by extending the Lazy Snapping [1] to 3D. A high-level painting tool is provided for the user to indicate which part is object and which is background in volume by marking some lines. The segmentation result can be determined with little interaction without voxel-precise selection. In order to improve the performance, we adopt the watershed used in [1] to pre-process the volume data. And we implement the 3D watershed to handle the volume data. However, large size of volume data still needs great computation. It is hard to achieve a real time response. To improve the efficiency without losing the accuracy, we introduce a volume of interest (VOI) specified by the user to restrict the data size for processing. Our system also implements a user-friendly interface to browse the volume of interest area in three cutting planes.
Description: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Oral session: Vision-based Information Processing and Applications (6 October 2009).
Conference Name: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議
Conference Place: Sapporo
Type: proceedings
URI: http://hdl.handle.net/2115/39714
Appears in Collections:北海道大学サステナビリティ・ウィーク2009 (Sustainability Weeks 2009) > 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 (2009 APSIPA Annual Summit and Conference)

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