Medical imaging and nuclear medicine: a Lancet Oncology Commission
The diagnosis and treatment of patients with cancer requires access to imaging to ensure
accurate management decisions and optimal outcomes. Our global assessment of imaging …
accurate management decisions and optimal outcomes. Our global assessment of imaging …
Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation
D Visvikis, P Lambin, K Beuschau Mauridsen… - European journal of …, 2022 - Springer
Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as
it will in everyday life. In this review, we focus on the potential applications of AI in the field …
it will in everyday life. In this review, we focus on the potential applications of AI in the field …
Deep learning–based image conversion of CT reconstruction kernels improves radiomics reproducibility for pulmonary nodules or masses
Background Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics
seeks to assess tumor features to provide detailed imaging features. However, CT radiomic …
seeks to assess tumor features to provide detailed imaging features. However, CT radiomic …
Inconsistent performance of deep learning models on mammogram classification
Objectives Performance of recently developed deep learning models for image classification
surpasses that of radiologists. However, there are questions about model performance …
surpasses that of radiologists. However, there are questions about model performance …
Improved trainable calibration method for neural networks on medical imaging classification
Recent works have shown that deep neural networks can achieve super-human
performance in a wide range of image classification tasks in the medical imaging domain …
performance in a wide range of image classification tasks in the medical imaging domain …
Automated door placement in architectural plans through combined deep-learning networks of ResNet-50 and Pix2Pix-GAN
Previous studies on automating building design with deep learning primarily focused on
planning room layouts, limiting the design of architectural elements such as doors and …
planning room layouts, limiting the design of architectural elements such as doors and …
Systematic review of advanced AI methods for improving healthcare data quality in post COVID-19 Era
At the beginning of the COVID-19 pandemic, there was significant hype about the potential
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …
Improving effectiveness of different deep learning-based models for detecting COVID-19 from computed tomography (CT) images
COVID-19 has caused a pandemic crisis that threatens the world in many areas, especially
in public health. For the diagnosis of COVID-19, computed tomography has a prognostic role …
in public health. For the diagnosis of COVID-19, computed tomography has a prognostic role …
Joint 2d-3d breast cancer classification
Breast cancer is the malignant tumor that causes the highest number of cancer deaths in
females. Digital mammograms (DM or 2D mammogram) and digital breast tomosynthesis …
females. Digital mammograms (DM or 2D mammogram) and digital breast tomosynthesis …
Alzheimer's disease classification using 2d convolutional neural networks
Alzheimer's disease (AD) is a non-treatable and non-reversible disease that affects about
6% of people who are 65 and older. Brain magnetic resonance imaging (MRI) is a pseudo …
6% of people who are 65 and older. Brain magnetic resonance imaging (MRI) is a pseudo …