access icon openaccess Classifying functional nuclear images with convolutional neural networks: a survey

Functional imaging has successfully been applied to capture functional changes in the pathological tissues of a body in recent years. Nuclear medicine functional imaging has been used to acquire information about areas of concerns (e.g. lesions and organs) in a non-invasive manner, enabling semi-automated or automated decision-making for disease diagnosis, treatment, evaluation, and prediction. Focusing on functional nuclear medicine images, in this study, the authors review existing work on the classification of single-photon emission computed tomography, positron emission tomography, and their hybrid modalities with computed tomography and magnetic resonance imaging images by using convolutional neural network (CNN) techniques. Specifically, they first present an overview of nuclear imaging and the CNN technique, such as nuclear imaging modalities, nuclear image data format, CNN architecture, and the main CNN classification models. According to the diseases of concern, they then classify the existing CNN-based work on the classification of functional nuclear images into three different categories. For the typical work in each of these categories, they present details about their research objectives, adopted CNN models, and achieved main results. Finally, they discuss research challenges and directions for developing technological solutions to classify nuclear medicine images based on the CNN technique.

Inspec keywords: convolutional neural nets; medical image processing; computerised tomography; image classification; diseases; single photon emission computed tomography; reviews; biomedical MRI; positron emission tomography; biological tissues

Other keywords: single-photon emission computed tomography; functional nuclear medicine images; convolutional neural networks; decision making; CNN classification models; magnetic resonance imaging images; pathological tissues; positron emission tomography; nuclear medicine functional imaging; disease

Subjects: X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); X-rays and particle beams (medical uses); Medical magnetic resonance imaging and spectroscopy; Computer vision and image processing techniques; Neural computing techniques; Biology and medical computing; Optical, image and video signal processing; Reviews and tutorial papers; resource letters; Nuclear medicine, emission tomography; Nuclear medicine, emission tomography; Biomedical magnetic resonance imaging and spectroscopy; Patient diagnostic methods and instrumentation

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