Key papers in Radiology, Nuclear Medicine and Imaging
Pofolia’s corpus holds 64 papers from the Radiology, Nuclear Medicine and Imaging subfield (2001–2023). The list below starts with the most cited.
Most cited
Ranked by citation count. Because citations accumulate over time, this list naturally leans towards work published a few years ago; for where the field is now, see “recently added”.
A default mode of brain function
Proceedings of the National Academy of Sciences · 2001 · Q1 · SJR 3.00 · FWCI 39.11 · 12,441 citations
A consistent baseline state of the adult human brain, characterized by a uniform oxygen extraction fraction (OEF), has been identified, with deviations primarily occurring as deactivations in the visual system during goal-directed tasks.
Radiomics: Images Are More than Pictures, They Are Data
Radiology · 2015 · Q1 · SJR 4.00 · FWCI 161.07 · 8,340 citations
Radiomics transforms medical images from visual aids into mineable data by extracting quantitative features, enabling sophisticated analysis for improved diagnostic and prognostic accuracy.
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
JAMA · 2016 · Q1 · SJR 5.00 · FWCI 395.63 · 7,615 citations
A deep learning algorithm achieved high accuracy in detecting referable diabetic retinopathy (RDR) from retinal fundus images, demonstrating a 0.991 AUC on one dataset and 0.990 on another.
2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes
European Heart Journal · 2019 · Q1 · SJR 5.00 · FWCI 515.68 · 7,178 citations · Open access
These guidelines provide a framework for diagnosing and managing chronic coronary syndromes (CCS), a condition characterized by atherosclerotic plaque buildup in heart arteries.
scikit-image: image processing in Python
PeerJ · 2014 · Q1 · FWCI 81.13 · 7,038 citations
scikit-image is a new open-source Python library providing a comprehensive set of image processing algorithms and utilities for research, education, and industry.
Computational Radiomics System to Decode the Radiographic Phenotype
Cancer Research · 2017 · Q1 · SJR 4.00 · FWCI 154.28 · 6,553 citations · Open access
A new open-source Python platform, PyRadiomics, has been developed to standardize the extraction of quantitative features from medical images for radiomic analysis.
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
IEEE Transactions on Medical Imaging · 2016 · Q1 · SJR 2.00 · FWCI 376.36 · 5,813 citations
This paper investigates how CNN architecture, dataset size, and transfer learning from natural images impact computer-aided detection (CADe) in medical imaging, achieving state-of-the-art results on lymph node detection.
Convolutional neural networks: an overview and application in radiology
Insights into Imaging · 2018 · Q1 · SJR 1.00 · FWCI 166.02 · 4,622 citations · Open access
Convolutional Neural Networks (CNNs), a powerful deep learning technique dominant in computer vision, are increasingly being explored for their potential to enhance radiological tasks.
2013 ESC guidelines on the management of stable coronary artery disease
European Heart Journal · 2013 · Q1 · SJR 5.00 · FWCI 313.34 · 4,538 citations
The 2013 ESC Guidelines offer recommendations for managing stable coronary artery disease, emphasizing their role as a guide for clinical judgment.
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping
Radiology · 2020 · Q1 · SJR 4.00 · FWCI 205.30 · 3,917 citations
This paper introduces the Image Biomarker Standardization Initiative (IBSI) aimed at standardizing radiomic feature extraction from medical images. The initiative provides a framework and reference for reproducible quantitative imaging analysis.
Optical properties of biological tissues: a review
Physics in Medicine and Biology · 2013 · Q2 · FWCI 145.18 · 3,885 citations
This review consolidates reported optical properties of biological tissues, detailing their wavelength-dependent scattering and absorption.
An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging
NeuroImage · 2015 · Q1 · SJR 1.00 · FWCI 89.35 · 3,826 citations
A new method retrospectively corrects for distortions caused by eddy currents and subject movement in diffusion MRI, improving data quality by registering volumes to a model-free prediction.
Fourth Universal Definition of Myocardial Infarction (2018)
Circulation · 2018 · Q1 · SJR 8.00 · FWCI 147.35 · 3,694 citations · Open access
This publication presents the 2018 Fourth Universal Definition of Myocardial Infarction, updating diagnostic criteria for heart attacks.
Adding Conditional Control to Text-to-Image Diffusion Models
2023 · 3,679 citations
ControlNet is a new neural network architecture that adds spatial conditioning controls to existing text-to-image diffusion models without altering their original weights.
Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study
The Lancet · 2012 · FWCI 218.37 · 3,675 citations
Children undergoing CT scans show an increased risk of leukaemia and brain tumours, with cumulative doses around 50-60 mGy nearly tripling the risk compared to doses under 5 mGy.
Current Protocols in Immunology
Current Protocols in Immunology · 2018 · 3,577 citations
Current Protocols in Immunology is a comprehensive, continuously updated manual detailing a wide range of immunological methods, from classic to cutting-edge.
ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases
2017 · 3,371 citations
Researchers created ChestX-ray8, a database of 108,948 chest X-rays from 32,717 patients, labeled with eight common diseases using natural language processing on radiology reports.
FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0
European Journal of Nuclear Medicine and Molecular Imaging · 2014 · Q1 · SJR 2.00 · FWCI 78.49 · 3,310 citations · Open access
These updated guidelines provide standardized procedures for FDG PET/CT in adult oncological imaging, focusing on harmonizing quantitative measurements for improved accuracy and reproducibility across different sites and systems.
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?
IEEE Transactions on Medical Imaging · 2016 · Q1 · SJR 2.00 · FWCI 210.18 · 3,223 citations
Fine-tuning pre-trained deep convolutional neural networks (CNNs) consistently matches or surpasses training from scratch for medical image analysis, even with limited data.
COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
Scientific Reports · 2020 · Q1 · FWCI 266.82 · 3,163 citations · Open access
Researchers developed COVID-Net, a novel open-source deep learning model specifically designed to detect COVID-19 from chest X-ray images, and released it alongside the COVIDx dataset.
Recently added
Adding Conditional Control to Text-to-Image Diffusion Models
2023 · 3,679 citations
ControlNet is a new neural network architecture that adds spatial conditioning controls to existing text-to-image diffusion models without altering their original weights.
UNETR: Transformers for 3D Medical Image Segmentation
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) · 2022 · 2,918 citations
UNETR, a novel U-shaped network, uses a transformer encoder to capture long-range spatial dependencies for 3D medical image segmentation, achieving new state-of-the-art performance on the BTCV dataset.
Artificial intelligence: A powerful paradigm for scientific research
The Innovation · 2021 · Q1 · SJR 3.00 · FWCI 108.21 · 1,608 citations · Open access
Artificial intelligence (AI) and machine learning (ML) are transforming scientific research by enabling analysis of high-throughput data for insights, predictions, and evidence-based decisions across disciplines like medicine, materials science, and physics.
2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines
Circulation · 2021 · Q1 · SJR 8.00 · FWCI 145.59 · 1,582 citations
New guidelines offer evidence-based algorithms for diagnosing chest pain in adults, incorporating cost-value analysis and shared decision-making.
COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images
Scientific Reports · 2020 · Q1 · FWCI 266.82 · 3,163 citations · Open access
Researchers developed COVID-Net, a novel open-source deep learning model specifically designed to detect COVID-19 from chest X-ray images, and released it alongside the COVIDx dataset.
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