NDLI: Automatic Localization of the Anterior Commissure, Posterior Commissure, and Midsagittal Plane in MRI Scans using Regression Forests

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Automatic Localization of the Anterior Commissure, Posterior Commissure, and Midsagittal Plane in MRI Scans using Regression Forests

Content Provider	PubMed Central
Author	Liu, Yuan Dawant, Benoit M.
Abstract	Localizing the anterior and posterior commissures (AC/PC) and the midsagittal plane (MSP) is crucial in stereotactic and functional neurosurgery, human brain mapping, and medical image processing. We present a learning-based method for automatic and efficient localization of these landmarks and the plane using regression forests. Given a point in an image, we first extract a set of multi-scale long-range contextual features. We then build random forests models to learn a nonlinear relationship between these features and the probability of the point being a landmark or in the plane. Three-stage coarse-to-fine models are trained for the AC, PC, and MSP separately using down-sampled by 4, down-sampled by 2, and the original images. Localization is performed hierarchically, starting with a rough estimation that is progressively refined. We evaluate our method using a leave-one-out approach with 100 clinical T1-weighted images and compare it to state-of-the-art methods including an atlas-based approach with six nonrigid registration algorithms and a model-based approach for the AC and PC, and a global symmetry-based approach for the MSP. Our method results in an overall error of 0.55±0.30mm for AC, 0.56±0.28mm for PC, 1.08°±0.66° in the plane’s normal direction and 1.22±0.73 voxels in average distance for MSP; it performs significantly better than four registration algorithms and the model-based method for AC and PC, and the global symmetry-based method for MSP. We also evaluate the sensitivity of our method to image quality and parameter values. We show that it is robust to asymmetry, noise, and rotation. Computation time is 25 seconds.
Related Links	http://dx.doi.org/10.1109/jbhi.2015.2428672
Ending Page	1374
Page Count	13
Starting Page	1362
File Format	PDF
ISSN	21682194
e-ISSN	21682208
Journal	IEEE journal of biomedical and health informatics
Issue Number	4
Volume Number	19
Language	English
Publisher Date	2015-07-01
Access Restriction	Open
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Health Information Management Health Informatics Electrical and Electronic Engineering Computer Science Applications Biotechnology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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