Efficient Variational Approach to Multimodal Registration of Anatomical and Functional Intra-Patient Tumorous Brain Data
| Autor: | Rafael Verdú-Monedero, Juan Morales-Sánchez, Valery Naranjo, Fernando López-Mir, Angela Bernabeu, Álvar-Ginés Legaz-Aparicio, Jorge Larrey-Ruiz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Computer Networks and Communications
Computer science Interface (computing) Image registration Neuroimaging Brain imaging Multimodal Imaging Surgical planning 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine TEORIA DE LA SEÑAL Y COMUNICACIONES Image Processing Computer-Assisted High spatial resolution Humans Computer vision Brain function Brain Mapping Modality (human–computer interaction) business.industry General Medicine Variational registration Frequency domain Multimodal registration Artificial intelligence business Brain registration Functional localization 030217 neurology & neurosurgery |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| Popis: | This paper addresses the functional localization of intra-patient images of the brain. Functional images of the brain (fMRI and PET) provide information about brain function and metabolism whereas anatomical images (MRI and CT) supply the localization of structures with high spatial resolution. The goal is to find the geometric correspondence between functional and anatomical images in order to complement and fuse the information provided by each imaging modality. The proposed approach is based on a variational formulation of the image registration problem in the frequency domain. It has been implemented as a C/C++ library which is invoked from a GUI. This interface is routinely used in the clinical setting by physicians for research purposes (Inscanner, Alicante, Spain), and may be used as well for diagnosis and surgical planning. The registration of anatomic and functional intra-patient images of the brain makes it possible to obtain a geometric correspondence which allows for the localization of the functional processes that occur in the brain. Through 18 clinical experiments, it has been demonstrated how the proposed approach outperforms popular state-of-the-art registration methods in terms of efficiency, information theory-based measures (such as mutual information) and actual registration error (distance in space of corresponding landmarks) |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|