Table 3 A brief summary of algorithms that were evaluated on the proposed framework
Algorithm | Technique | Evaluation | Atrial wall | Strengths | Weaknesses |
|---|---|---|---|---|---|
IC: Bai et al. | Hysteresis thresholding | 30 pre and post | Euclidean distance - 3 mm | Coherent segmentations | Fixed sigmoid models derived from empirical data |
MV: Hennemuth et al. | Region-growing with EM-fitting | 30 pre and post | Euclidean distance - 3 mm | Post ablation imaging | Pre-ablation imaging |
SY: Lu et al. | MRF model with graph-cuts | 20 pre and post | Dilation - 4 mm | Fuzzy membership - improved delineation | Post-processing for small cluster removal |
HB: Gao et al. | Active contour and EM-fitting | 15 post | Active contour (snake) | Accurate myocardial segmentation | Fixed number of gaussian mixtures in model (i.e. two) |
YL: Peters et al. | Simple thresholding | 15 pre and post | Manual | Accurate segmentation on both pre- and post. | Time consuming |
KCL: Karim et al. | MRF model with graph-cuts | 30 pre and post | Post-ablation imaging | Pre-ablation imaging | Post-processing steps necessary |
UTA: Cates et al. | Histogram analysis and simple thresholding | 30 pre and post | Manual | Accurate segmentation on pre and post. | Time consuming |
UTB: Perry et al. | k-means clustering | 30 pre and post | Manual | Pre-ablation fibrosis | Equivalent variance across all clusters - LA scar variance more variable |