This paper tries to give a gentle introduction to deep learning in medical image processing,
proceeding from theoretical foundations to applications. We first discuss general reasons for …

Artificial intelligence (AI) as an emerging technology is gaining momentum in medical
imaging. Recently, deep learning-based AI techniques have been actively investigated in …

Deep learning has attracted rapidly increasing attention in the field of tomographic image
reconstruction, especially for CT, MRI, PET/SPECT, ultrasound and optical imaging. Among …

Photoacoustic imaging is an emerging imaging modality that is based upon the
photoacoustic effect. In photoacoustic tomography (PAT), the induced acoustic pressure …

Over past several years, machine learning, or more generally artificial intelligence, has
generated overwhelming research interest and attracted unprecedented public attention. As …

The purpose of this research was to implement a deep learning network to overcome two of
the major bottlenecks in improved image reconstruction for clinical positron emission …

Score-based generative model (SGM) has risen to prominence in sparse-view CT
reconstruction due to its impressive generation capability. The consistency of data is crucial …

Computed tomography (CT) is an imaging modality widely used for medical diagnosis and
treatment. CT images are often corrupted by undesirable artifacts when metallic implants are …

Low dose computed tomography (LDCT) has attracted more and more attention in routine
clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray …

Computed tomography (CT) has been widely used for medical diagnosis, assessment, and
therapy planning and guidance. In reality, CT images may be affected adversely in the …