Auto-segmentation of Hemi-Diaphragms in Free-Breathing Pediatric Dynamic MRI

Quantitative analysis of the regional motion of the left hemi-diaphragm (LHD) and right hemi-diaphragm (RHD) can provide information regarding the distribution and severity of abnormalities in individual patients with conditions that affect respiration such as thoracic insufficiency syndrome (TIS). Such motion can be captured effectively from dynamic magnetic resonance imaging (dMRI) which does not involve ionizing radiation and can be obtained under free-breathing conditions. The analysis of motion can be performed on the diaphragm using 4D images constructed from dMRI, which in turn requires diaphragm segmentation in the 4D images. In this paper, we present our methodology for segmentation of the left and right diaphragms, which has been implemented in three steps: recognition of diaphragm, delineation of diaphragm, and splitting of diaphragm along the mid-sagittal plane into LHD and RHD. The challenges involved in dMRI images are low resolution, motion blur, suboptimal contrast resolution, inconsistent meaning of gray-level intensities for the same object across multiple scans, and low signal-to-noise ratio. Utilizing 200 and 100 3D images for training and testing, respectively, an average location error of one and a half voxels is achieved for the recognition step. For the delineation step, an average mean-HD of one and a half pixels is achieved. The mid-sagittal plane is identified within a quarter of a voxel. These results are promising, showing that our system can cope with the aforesaid challenges.