Shuo Li

Stefanie Speidel

Linwei Wang

Qi Dou

P. Thomas Fletcher

The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging; Part III: Breast imaging; colonoscopy; computer aided diagnosis; Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I; Part V: Image segmentation II; integration of imaging with non-imaging biomarkers; Part VI: Image registration; image reconstruction; Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization; Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part VI

Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part V

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part III

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part II

Maria S. Guillem

Carlos Figuera

Electrical activity in the myocardium coordinates the contraction of the heart, and its knowledge could lead to a better understanding, diagnosis, and treatment of cardiac diseases. This electrical activity generates an electromagnetic field that propagates outside the heart and reaches the human torso surface, where it can be easily measured. Classical electrocardiography aims to interpret the 12-lead electrocardiogram (ECG) to determine cardiac activity and support the diagnosis of cardiac pathologies such as arrhythmias, altered activations, and ischemia. More recently, a higher number of leads is used to reconstruct a more detailed quantitative description of the electrical activity in the heart by solving the so-called inverse problem of electrocardiography. This technique is known as ECG imaging. Today, clinical applications of ECG imaging are showing promising results in guiding a variety of electrophysiological interventions such as catheter ablation of atrial fibrillation and ventricular tachycardia. However, in order to promote the adoption of ECG imaging in the routine clinical practice, further research is required regarding more accurate mathematical methods, further scientific validation under different preclinical scenarios and a more extensive clinical validation

Electrocardiographic Imaging

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part VII

Linwei Wang

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