Pranav Bhagirath

69 Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images segment infarct that has contiguous regions. However, key considerations such as the shape of candidate regions, are not always taken into account. UPF searches for regions that are elongated, as this is a strong characteristic of LV infarcts. A second important consideration is the seed selection step. If only a single seed is allowed per slice for capturing the infarct (for example UPF, see Table 3 ), other infarct areas on the same slice cannot be included. The average number of infarct regions per slice was computed for both patient and porcine datasets in Table 6 . With the average number of regions found to be 1.2 in the patient dataset, more than a single seed may be necessary. A second consideration is the spatial positioning of the scar candidate in relation to the image slices or 17-segment model of the AHA (Cerqueira et al., 2002). Enhancement in the basal slices due to the outflow tract or RV insertion point should be discriminated as a pseudo infarct. None of the algorithms or fixed models, have classified enhancement based on its location. Thus, pseudo infarcts have not been addressed in the evaluated methods. A third consideration is the extent of scarring. Sub-classification of infarct as sub- endocardial, mid-wall and epicardial helps stratify treatment. But first and foremost, these formations are indicative of scar, one which the algorithms should be able to distinguish based on Euclidean distances measured on the myocardium segmentation. Equipped with this information, algorithms should be able to better distinguish scar, especially when enhancements arise due to partial voluming or a fat-related cause. LGE CMR for the LV can be acquired either in 2D or 3D, with the former being more common as they can be obtained relatively quickly. However, 3D acquisitions are preferred over 2D when post-processing involves detailed quantification. As scanner engineering and technology continue to improve, 3D acquisitions will become more common. All algorithms, except UPF, evaluated within this framework and those surveyed in Table 1 uses 3D techniques that also work on 2D datasets. The UPF technique performs region-growing with seed selection on a slice-by-slice basis. For the porcine 3D datasets, it chooses a particular slice orientation (x, y or z) to work on; and an increasing load on the operator for seed-selection in each 3D slice. The framework supplies with both types of acquisitions to enable future algorithms to be evaluated separately. Future algorithms Infarct quantification in the LV is an important assessment criterion for many cardiac therapies. Furthermore, heterogeneity within infarct, especially in the peri-infarct regions, was shown to be a predictor of tachycardia and sudden cardiac death (Schmidt