… Xiang et al demonstrated a convolutional neural network (CNN) architecture that … -PET
image along with a T1-weighted MR image to output a significantly denoised FDG-PET image. …

… for PET image … artificial intelligence (AI), the fields of medical image reconstruction and
processing have been revolutionized by the availability of a new generation of AI-powered image …

… from a PET scan (this set is often referred to as the manifold). For example, we know a PET
scan can never deliver a CT or MR image, let alone a natural photographic image. Yet the …

… processing and machine/deep learning techniques to PET/CT imaging with special focus on
the oncological radiotherapy domain as a case study and draw examples from our work and …

… the field of machine learning and artificial intelligence (AI) centered around … image quality
for PET imaging directly and how the additional use of anatomic information from CT and MRI …

… special regards to artificial intelligence (AI) on medical images (CT, MRI, PET) are under …
information related to the reconstruction of imaging, the segmentation of tissues acquired, the …

… This review sets out to discuss the foremost applications of artificial intelligence (AI), … (PET)
imaging. To this end, the underlying limitations/challenges of these imaging modalities are …

… count PET images, with near-to or nondiagnostic images at higher dose reduction levels (up
to 6.25%), both SwinIR and U-Net significantly improve the diagnostic quality of PET images…

… methods for PET imaging. Five different ways that deep learning-based methods can aid PET
… By using the high-resolution computed tomographic (CT) and MR images, anatomic priors …

… emergence of artificial intelligence (AI) in computer vision (ie, convolutional neural network
(… due to a misalignment between PET and MR images or motion artifacts caused by rigid or …