NDLI: Anatomical Model-Guided Segmentation of Brain MR Image Sequences

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Anatomical Model-Guided Segmentation of Brain MR Image Sequences

Content Provider	ACM Digital Library
Author	Mondal, Prasenjit Sural, Shamik Bhattacharyya, Pinak Pani Mukhopadhyay, Jayanta
Abstract	This paper presents a method for segmentation of human brain magnetic resonance (MR) image sequences based on a 3D human brain model (triangulated mesh). The brain model is composed of four components, namely, cerebrum, cerebellum, brain stem and pituitary gland. Synthesized image sequences are extracted from the model at regular intervals for sagittal and coronal views as done in MR imaging. To align a series of real MR images with these synthesized cross-sections, an efficient dynamic programming based computational technique has been used that obtains the optimal synthesized cross-section sequence corresponding to the series of MR images. For automatic segmentation of anatomical structures from the MR images, each aligned synthesized cross-section is overlaid on the corresponding physical MR image by carrying out appropriate geometric transformation. This transformation produces model guided boundaries for four segments corresponding to cerebrum, cerebellum, brain stem and pituitary gland. Subsequently, these initial contours are further refined by the method of active contouring, which provides segmentation of 3D MR images into the above mentioned four parts. The proposed method compares well with the recently proposed Charged Fluid Model (CFM) based approach and level set segmentation method in terms of accuracy at a significantly lower computational cost.
Starting Page	1
Ending Page	8
Page Count	8
File Format	PDF
ISBN	9781450330619
DOI	10.1145/2683483.2683491
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-12-14
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Image segmentation Active contouring Brain mr images Brain model
Content Type	Text
Resource Type	Article

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