eprintid: 3595 rev_number: 6 eprint_status: archive userid: 69 dir: disk0/00/00/35/95 datestamp: 2016-11-14 11:24:12 lastmod: 2016-11-14 11:24:12 status_changed: 2016-11-14 11:24:12 type: book_section metadata_visibility: show creators_name: Sevetlidis, Vasileios creators_name: Giuffrida, Mario Valerio creators_name: Tsaftaris, Sotirios A. creators_id: creators_id: valerio.giuffrida@imtlucca.it creators_id: title: Whole Image Synthesis Using a Deep Encoder-Decoder Network ispublished: pub subjects: QA76 subjects: T1 divisions: CSA full_text_status: none abstract: The synthesis of medical images is an intensity transformation of a given modality in a way that represents an acquisition with a different modality (in the context of MRI this represents the synthesis of images originating from different MR sequences). Most methods follow a patch-based approach, which is computationally inefficient during synthesis and requires some sort of ‘fusion’ to synthesize a whole image from patch-level results. In this paper, we present a whole image synthesis approach that relies on deep neural networks. Our architecture resembles those of encoder-decoder networks, which aims to synthesize a source MRI modality to an other target MRI modality. The proposed method is computationally fast, it doesn’t require extensive amounts of memory, and produces comparable results to recent patch-based approaches. date: 2016 date_type: published series: Lecture Notes in Computer Science number: 9968 publisher: Springer International Publishing pagerange: 127-137 pages: 11 id_number: 10.1007/978-3-319-46630-9_13 refereed: TRUE isbn: 978-3-319-46629-3 book_title: Simulation and Synthesis in Medical Imaging. First International Workshop, SASHIMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings official_url: http://dx.doi.org/10.1007/978-3-319-46630-9_13 citation: Sevetlidis, Vasileios and Giuffrida, Mario Valerio and Tsaftaris, Sotirios A. Whole Image Synthesis Using a Deep Encoder-Decoder Network. In: Simulation and Synthesis in Medical Imaging. First International Workshop, SASHIMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings. Lecture Notes in Computer Science (9968). Springer International Publishing, pp. 127-137. ISBN 978-3-319-46629-3 (2016)