Model-based automatic detection of the anterior and posterior commissures on MRI scans

Abstract

The projections of the anterior and posterior commissures (AC/PC) on the mid-sagittal plane of the human brain are important landmarks in neuroimaging. They can be used, for example, during MRI scanning for acquiring the imaging sections in a standard orientation. In post-acquisition image processing, these landmarks serve to establish an anatomically-based frame of reference within the brain that can be extremely useful in designing automated image analysis algorithms such as image segmentation and registration methods. This paper presents a fully automatic model-based algorithm for AC/PC detection on MRI scans. The algorithm utilizes information from a number of model images on which the locations of the AC/PC and a reference point (the vertex of the superior pontine sulcus) are known. This information is then used to locate the landmarks on test scans by template matching. The algorithm is designed to be fast, robust, and accurate. The method is flexible in that it can be trained to work on different image contrasts, optimized for different populations, or scanning modes. To assess the effectiveness of this technique, we compared automatically and manually detected landmark locations on 84 T1-weighted and 42 T2-weighted test scans. Overall, the average Euclidean distance between automatically and manually detected landmarks was 1.1 mm. A software implementation of the algorithm is freely available online at www.nitrc.org/projects/art.

Corpus Callosum Shape and Size Changes in Early Alzheimer's Disease: A Longitudinal MRI Study Using the OASIS Brain Database

“…Segmentation of the CC on the mid-sagittal section of the brain was accomplished using the Automatic Registration Toolbox (ART) software module ‘yuki’ (http://www.nitrc.org/projects/art) in four automatic steps: 1) Location of the mid-sagittal plane (MSP) [18]; 2) Location of the anterior and posterior commissures (AC and PC) on the MSP [19]; 3) Standardized reorientation and interpolation of the MSP to 512×512 pixels of size 0.5×0.5 mm 2 ; and 4) Two-dimensional model-based segmentation of the CC on the standardized MSP [20]. …”

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

“…For example, in [6], [9]–[11], the corpus callosum was used to initialize the AC and PC positions. Ardekani et al [12] achieved the initialization by identifying the MSP and a landmark on the midbrain-pons junctions. Han et al [6] and Verard et al [9] also relied on edge detection.…”

The effectiveness of geometry features on multi-resolution diffeomorphic demons registration in the implementation of human cortex surface parcellation

“…The preprocessing steps included: 1) automated identification of the anterior (AC) and posterior commisure (PC) [7], 2) spatial AC-PC alignment, 3) multi-modal image registration, 4) bias field correction, 5) tissue classification [8], and 6) neural network based definition of the subcortical structures and brain mask [9], 7) definition of left and right hemispheres by registering the subject image with the atlas image using diffeomorphic demons algorithm.…”