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Accurate cardiac computing, analysis and modeling from multi-modality images are important for the diagnosis and treatment of cardiac disease. Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is a promising technique to visualize and quantify myocardial infarction (MI) and atrial scars. Automating quantification of MI and atrial scars can be challenging due to the low image quality and complex enhancement patterns of LGE MRI. Moreover, compared with the other sequences LGE MRIs with gold standard labels are particularly limited, which represents another obstacle for developing novel algorithms for automatic segmentation and quantification of LGE MRIs. This chapter aims to summarize the state-of-the-art and our recent advanced contributions on deep learning based multi-modality cardiac image analysis. Firstly, we introduce two benchmark works for multi-sequence cardiac MRI based myocardial and pathology segmentation. Secondly, two novel frameworks for left atrial scar segmentation and quantification from LGE MRI were presented. Thirdly, we present three unsupervised domain adaptation techniques for cross-modality cardiac image segmentation., Comment: Under review as a chapter of book 'Deep Learning for Medical Image Analysis, 2E'

Drawing upon a study of individuals who have outgrown their membership of the Chinese hip-hop fan community, we contribute to the theorisation of nonlinear and amorphous identity dynamics within CCT through introducing the concept of the vestigial self. We explore how vestiges of individuals’ micro-culturally forged identities persevere long after individuals have transitioned away from identification with particular communities. Through unpacking the continuity, synthesis and operation of various vestiges of who they “used to be” including fantasies, sexual scripts and cultural narcissism, we discuss how consumers improvise links between former, current and possible selves to negotiate social interactions across time and place. Here, we unpick the micro and macro catalysts, turning points and transitions that reactivate imprints of individuals’ former identifications and ideological orientations. This allows us to theorise the vestigial self as an existential long shadow which accompanies consumers as they navigate through the course of their lives.

Drawing upon a study of individuals who have outgrown their membership of the Chinese hip-hop fan community, we contribute to the theorisation of nonlinear and amorphous identity dynamics within CCT through introducing the concept of the vestigial self. We explore how vestiges of individuals’ micro-culturally forged identities persevere long after individuals have transitioned away from identification with particular communities. Through unpacking the continuity, synthesis and operation of various vestiges of who they “used to be” including fantasies, sexual scripts and cultural narcissism, we discuss how consumers improvise links between former, current and possible selves to negotiate social interactions across time and place. Here, we unpick the micro and macro catalysts, turning points and transitions that reactivate imprints of individuals’ former identifications and ideological orientations. This allows us to theorise the vestigial self as an existential long shadow which accompanies consumers as they navigate through the course of their lives.