Evaluation of Deep Learning–Based Approaches to Segment Bowel Air Pockets and Generate Pelvic Attenuation Maps from CAIPIRINHA-Accelerated Dixon MR Images - Sari, Hasan; Reaungamornrat, Ja; Catalano, Onofrio A.; Vera-Olmos, Javier; Izquierdo-Garcia, David; Morales, Manuel A.; Torrado-Carvajal, Angel; Ng, Thomas S.C.; Malpica, Norberto; Kamen, Ali; Catana, Ciprian (Journal of Nuclear Medicine, 2022)
Keywords: Air pockets; Artificial neural networks; Attenuation; Clinical Investigation; Computed tomography; Deep Learning; Gastrointestinal tract; Humans; Image processing; Image Processing, Computer-Assisted - methods; Image reconstruction; Image segmentation; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Medical imaging; Neural networks; Pelvis; Pelvis - diagnostic imaging; Positron emission; Positron emission tomography; Positron-Emission Tomography - methods; Synthesis; Tomography; Tomography, X-Ray Computed; pseudo-CT; deep learning; PET/MRI; attenuation correction; PET quantification