Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy

H Arabi, H Zaidi - European Journal of Hybrid Imaging, 2020 - Springer
This brief review summarizes the major applications of artificial intelligence (AI), in particular
deep learning approaches, in molecular imaging and radiation therapy research. To this …

Learning to exploit temporal structure for biomedical vision-language processing

S Bannur, S Hyland, Q Liu… - Proceedings of the …, 2023 - openaccess.thecvf.com
Self-supervised learning in vision--language processing (VLP) exploits semantic alignment
between imaging and text modalities. Prior work in biomedical VLP has mostly relied on the …

Adaptive radiation therapy in the treatment of lung cancer: An overview of the current state of the field

H Piperdi, D Portal, SS Neibart, NJ Yue… - Frontiers in …, 2021 - frontiersin.org
Lung cancer treatment is constantly evolving due to technological advances in the delivery
of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment …

GP-GAN: Brain tumor growth prediction using stacked 3D generative adversarial networks from longitudinal MR Images

A Elazab, C Wang, SJS Gardezi, H Bai, Q Hu, T Wang… - Neural Networks, 2020 - Elsevier
Brain tumors are one of the major common causes of cancer-related death, worldwide.
Growth prediction of these tumors, particularly gliomas which are the most dominant type …

Robust-Deep: a method for increasing brain imaging datasets to improve deep learning models' performance and robustness

A Sanaat, I Shiri, S Ferdowsi, H Arabi, H Zaidi - Journal of Digital Imaging, 2022 - Springer
A small dataset commonly affects generalization, robustness, and overall performance of
deep neural networks (DNNs) in medical imaging research. Since gathering large clinical …

Deep learning of longitudinal mammogram examinations for breast cancer risk prediction

S Dadsetan, D Arefan, WA Berg, ML Zuley, JH Sumkin… - Pattern recognition, 2022 - Elsevier
Abstract Information in digital mammogram images has been shown to be associated with
the risk of develo** breast cancer. Longitudinal breast cancer screening mammogram …

CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation

N Ebadi, R Li, A Das, A Roy, P Nikos, P Najafirad - Medical Image Analysis, 2023 - Elsevier
Adaptive radiotherapy (ART) is an advanced technology in modern cancer treatment that
incorporates progressive changes in patient anatomy into active plan/dose adaption during …

[HTML][HTML] Patient specific deep learning based segmentation for magnetic resonance guided prostate radiotherapy

S Fransson, D Tilly, R Strand - Physics and Imaging in Radiation Oncology, 2022 - Elsevier
Abstract Background and Purpose Treatments on combined Magnetic Resonance (MR)
scanners and Linear Accelerators (Linacs) for radiotherapy, called MR-Linacs, often require …

Synergizing medical imaging and radiotherapy with deep learning

H Shan, X Jia, P Yan, Y Li, H Paganetti… - … Learning: Science and …, 2020 - iopscience.iop.org
This article reviews deep learning methods for medical imaging (focusing on image
reconstruction, segmentation, registration, and radiomics) and radiotherapy (ranging from …

Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning

T Zhou, A Noeuveglise, R Modzelewski… - … Medical Imaging and …, 2023 - Elsevier
Brain tumor is one of the leading causes of cancer death. The high-grade brain tumors are
easier to recurrent even after standard treatment. Therefore, develo** a method to predict …