An overview of artificial intelligence in oncology

E Farina, JJ Nabhen, MI Dacoregio, F Batalini… - Future science …, 2022 - Taylor & Francis
Cancer is associated with significant morbimortality globally. Advances in screening,
diagnosis, management and survivorship were substantial in the last decades, however …

Clinical applications of artificial intelligence in radiology

C Mello-Thoms, CAB Mello - The British Journal of Radiology, 2023 - academic.oup.com
The rapid growth of medical imaging has placed increasing demands on radiologists. In this
scenario, artificial intelligence (AI) has become an attractive partner, one that may …

Nuclear medicine and artificial intelligence: best practices for algorithm development

TJ Bradshaw, R Boellaard, J Dutta, AK Jha… - Journal of Nuclear …, 2022 - Soc Nuclear Med
The nuclear medicine field has seen a rapid expansion of academic and commercial interest
in develo** artificial intelligence (AI) algorithms. Users and developers can avoid some of …

PET molecular imaging: a holistic review of current practice and emerging perspectives for diagnosis, therapeutic evaluation and prognosis in clinical oncology

V Duclos, A Iep, L Gomez, L Goldfarb… - International journal of …, 2021 - mdpi.com
PET/CT molecular imaging has been imposed in clinical oncological practice over the past
20 years, driven by its two well-grounded foundations: quantification and radiolabeled …

Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise

A Mehranian, SD Wollenweber, MD Walker… - European journal of …, 2022 - Springer
Purpose To enhance the image quality of oncology [18F]-FDG PET scans acquired in
shorter times and reconstructed by faster algorithms using deep neural networks. Methods …

Artificial intelligence-based image enhancement in pet imaging: Noise reduction and resolution enhancement

J Liu, M Malekzadeh, N Mirian, TA Song, C Liu… - PET clinics, 2021 - pet.theclinics.com
PET is a noninvasive molecular imaging modality that is increasingly popular in oncology,
neurology, cardiology, and other fields. 1–3 Accurate quantitation of PET radiotracer uptake …

Deep‐TOF‐PET: Deep learning‐guided generation of time‐of‐flight from non‐TOF brain PET images in the image and projection domains

A Sanaat, A Akhavanalaf, I Shiri, Y Salimi… - Human brain …, 2022 - Wiley Online Library
We aim to synthesize brain time‐of‐flight (TOF) PET images/sinograms from their
corresponding non‐TOF information in the image space (IS) and sinogram space (SS) to …

Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT

K Weyts, C Lasnon, R Ciappuccini, J Lequesne… - European journal of …, 2022 - Springer
Purpose We investigated whether artificial intelligence (AI)-based denoising halves PET
acquisition time in digital PET/CT. Methods One hundred ninety-five patients referred for …

Advances in PET/CT technology: an update

N Aide, C Lasnon, C Desmonts, IS Armstrong… - Seminars in nuclear …, 2022 - Elsevier
This article reviews the current evolution and future directions in PET/CT technology
focusing on three areas: time of flight, image reconstruction, and data-driven gating. Image …

Deep learning-based PET image denoising and reconstruction: a review

F Hashimoto, Y Onishi, K Ote, H Tashima… - … physics and technology, 2024 - Springer
This review focuses on positron emission tomography (PET) imaging algorithms and traces
the evolution of PET image reconstruction methods. First, we provide an overview of …