Pranav Bhagirath

46 Chapter 3 that constraints can be placed on the resulting segmentation, allowing segmentation boundary regularization with region-based properties. It also predicts which pixels are statistically most likely to be infarct based on prior probability distribution models. PROPOSED EVALUATION FRAMEWORK In this paper we propose an evaluation framework for future algorithms that segment and quantify infarct from LGE CMR images of the LV. To demonstrate the framework, five algorithms were evaluated by comparing against a consensus segmentation of experienced observers. The algorithm and observers were both provided the myocardium segmentation. The algorithms were also provided with training data sets. Algorithms evaluated in this work were submitted as a response to the open challenge, put forth to the medical imaging community at the Medical Image Computing and Computer Assisted Intervention (MICCAI) annual meeting’s workshop entitled as Delayed Enhancement MRI segmentation challenge. There were thirty LGE CMR data of the LV from both human and porcine cohorts used for the challenge. The data were divided into test (n = 20) and training (n = 10) sets. Each participant designed and implemented an algorithm which segmented the infarct in each dataset. The datasets are publicly available via the Cardiac Atlas project challenge website https: //www. cardiacatlas.org/web/guest/ventricular-infarction-challenge MATERIAL AND METHODS Data acquisition database LGE images were collected from two imaging centers: Imaging Sciences at King’s College London (KCL-IM) and Universiteit Leuven (UL). A total of fifteen human and fifteen porcine datasets were collected, of which five in each cohort were used as a training set for the algorithms. For all datasets, a short-axis stack of DE-MRI images covering the LV were provided. The myocardial mask in each image was made available. This was delineated carefully by an expert observer using short-axis slices. A first step was to determine the basal, mid and apical slices based on the standard American Heart Association (AHA) guidelines (Cerqueira et al., 2002). The contours for epicardial and endocardial borders, excluding the papillary muscles, were carefully drawn on each slice before the enclosed region in between them was filled to produce the mask. The images in the database were limited to the above two different types but varied in their quality. Refer to Table 2 for a summary of the two different types of data that were included in this study.