{'fraction_non_alphanumeric': 0.018867924528301886, 'fraction_numerical': 0.0, 'mean_word_length': 5.3, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Multi-modal data fusion for Cardiac Resynchronization Therapy planning and assistance

Cardiac Resynchronization Therapy (CRT) has been validated as an efficient treatment for selected patients suffering from heart failure with cardiac dyssynchrony. In case of bi-ventricular stimulation, the response to the therapy may be improved by an optimal choice of the left ventricle (LV) pacing sites. The characterization of LV properties to select the best candidate sites and to precise their access modes would be useful for the clinician in pre- and per-operative stages. For that purpose, we propose a new pre-operative analysis solution integrating previously developed multi-modal data registration methods and a new segmentation process of their coronary venous access. Moreover, a novel visualization interface is proposed to help the clinician to visualize the most relevant pacing sites and their access during the implantation in the operating room. This work is illustrated on real CRT data patients.