AIMC Topic: Diagnostic Imaging

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Early cancer detection using deep learning and medical imaging: A survey.

Critical reviews in oncology/hematology
Cancer, characterized by the uncontrolled division of abnormal cells that harm body tissues, necessitates early detection for effective treatment. Medical imaging is crucial for identifying various cancers, yet its manual interpretation by radiologis...

Space Radiology: Emerging Nonsonographic Medical Imaging Techniques and the Potential Applications for Human Spaceflight.

Wilderness & environmental medicine
Space medicine is a multidisciplinary field that requires the integration of medical imaging techniques and expertise in diagnosing and treating a wide range of acute and chronic conditions to maintain astronaut health. Medical imaging within this do...

Continual learning in medical image analysis: A survey.

Computers in biology and medicine
In the dynamic realm of practical clinical scenarios, Continual Learning (CL) has gained increasing interest in medical image analysis due to its potential to address major challenges associated with data privacy, model adaptability, memory inefficie...

The knowledge and perception of patients in Malta towards artificial intelligence in medical imaging.

Journal of medical imaging and radiation sciences
INTRODUCTION: Artificial intelligence (AI) is becoming increasingly implemented in radiology, especially in image reporting. Patients' perceptions about AI integration in medical imaging is a relatively unexplored area that has received limited inves...

Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

AJR. American journal of roentgenology
Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligenc...

Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review.

Journal of medical systems
In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the selection of appropriate computational models is critical for accurate diagnosis and patient care. This literature review provides a comprehensive com...

Generative AI in oncological imaging: Revolutionizing cancer detection and diagnosis.

Oncotarget
Generative AI is revolutionizing oncological imaging, enhancing cancer detection and diagnosis. This editorial explores its impact on expanding datasets, improving image quality, and enabling predictive oncology. We discuss ethical considerations and...

From code sharing to sharing of implementations: Advancing reproducible AI development for medical imaging through federated testing.

Journal of medical imaging and radiation sciences
BACKGROUND: The reproducibility crisis in AI research remains a significant concern. While code sharing has been acknowledged as a step toward addressing this issue, our focus extends beyond this paradigm. In this work, we explore "federated testing"...

Pilot deployment of a cloud-based universal medical image repository in a large public health system: A protocol study.

PloS one
This paper outlines the protocol for the deployment of a cloud-based universal medical image repository system. The proposal aims not only at the deployment but also at the automatic expansion of the platform, incorporating Artificial Intelligence (A...

Interactive dual-stream contrastive learning for radiology report generation.

Journal of biomedical informatics
Radiology report generation automates diagnostic narrative synthesis from medical imaging data. Current report generation methods primarily employ knowledge graphs for image enhancement, neglecting the interpretability and guiding function of the kno...