RT info:eu-repo/semantics/article
T1 Multi-device parallel MRI reconstruction: Efficient partitioning for undersampled 5D cardiac CINE
A1 López Ales, Emilio
A1 Menchón Lara, Rosa María
A1 Simmross Wattenberg, Federico Jesús
A1 Rodríguez Cayetano, Manuel
A1 Martín Fernández, Marcos Antonio
A1 Alberola López, Carlos
K1 Cardiology
K1 Magnetic resonance
K1 Resonancia magnética
K1 Cardiac imaging
K1 Heart - Magnetic resonance imaging
K1 Corazón - Enfermedades - Tratamiento
K1 Heart - Diseases - Treatment
K1 Computers
K1 Graphics processing units
K1 Image processing
K1 Imágenes, Tratamiento de las
K1 Compressed sensing (Telecommunication)
K1 Medical technology
K1 32 Ciencias Médicas
K1 3205.01 Cardiología
K1 3304 Tecnología de Los Ordenadores
K1 3325 Tecnología de las Telecomunicaciones
K1 3314 Tecnología Médica
AB Cardiac CINE, a form of dynamic cardiac MRI, is indispensable in the diagnosis and treatment of heart conditions, offering detailed visualization essential for the early detection of cardiac diseases. As the demand for higher-resolution images increases, so does the volume of data requiring processing, presenting significant computational challenges that can impede the efficiency of diagnostic imaging. Our research presents an approach that takes advantage of the computational power of multiple Graphics Processing Units (GPUs) to address these challenges. GPUs are devices capable of performing large volumes of computations in a short period, and have significantly improved the cardiac MRI reconstruction process, allowing images to be produced faster. The innovation of our work resides in utilizing a multi-device system capable of processing the substantial data volumes demanded by high-resolution, five-dimensional cardiac MRI. This system surpasses the memory capacity limitations of single GPUs by partitioning large datasets into smaller, manageable segments for parallel processing, thereby preserving image integrity and accelerating reconstruction times. Utilizing OpenCL technology, our system offers adaptability and cross-platform functionality, ensuring wider applicability. The proposed multi-device approach offers an advancement in medical imaging, accelerating the reconstruction process and facilitating faster and more effective cardiac health assessment.
PB MDPI
SN 1424-8220
YR 2024
FD 2024
LK https://uvadoc.uva.es/handle/10324/68076
UL https://uvadoc.uva.es/handle/10324/68076
LA eng
NO Sensors, 2024, Vol. 24, Nº. 4, 1313
NO Producción Científica
DS UVaDOC
RD 27-dic-2024