Pranav Bhagirath

63 Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images average than other methods at 21 and 23%, respectively of pseudo infarct labeled by the observers. This is in comparison to MV, AIT and UPF with only 3, 9 and 3%, respectively. Fixedmodels 2, 3, 4, 5, 6-SD and FWHM contained 53, 44, 36, 30, 24 and 23% respectively of manually labeled pseudo infarct volume. Pseudo infarcts were most successfully avoided in the MV and UPF algorithms and least in the 2, 3, 4 and 5-SD methods. Image quality on segmentation The LGE CMR images in the database were acquired at different imaging centers with differing protocols and scanners (see Table 2 ). The quality of enhancement is known to vary and it depends on a number of factors including optimal inversion times, signal-to-noise and contrast-to-noise (CNR) ratios. The images in the database were qualitatively rated by five observers experienced in LGE. Images were rated as poor, average or good depending on the overall quality of the image. The Dice overlap was measured separately in each category and these are given in Table 5 . In both the good and average categories, there were 40%, 60% from the patient and porcine datasets respectively; in the poor category, there were 75%, 25% from the patient and porcine datasets, respectively. A representative set of images for eachquality is shown in figure9 . Figure 9. Images in the patient and porcine datasets that are representative of good, average and poor quality images. The arrow labels indicate sites of possible infarction as labeled by an observer. There are two images shown for every quality.