AIMC Topic: Diagnostic Imaging

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EndoViT: pretraining vision transformers on a large collection of endoscopic images.

International journal of computer assisted radiology and surgery
PURPOSE: Automated endoscopy video analysis is essential for assisting surgeons during medical procedures, but it faces challenges due to complex surgical scenes and limited annotated data. Large-scale pretraining has shown great success in natural l...

A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey.

Journal of imaging informatics in medicine
In recent years, the role of Artificial Intelligence (AI) in medical imaging has become increasingly prominent, with the majority of AI applications approved by the FDA being in imaging and radiology in 2023. The surge in AI model development to tack...

Deep local-to-global feature learning for medical image super-resolution.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical images play a vital role in medical analysis by providing crucial information about patients' pathological conditions. However, the quality of these images can be compromised by many factors, such as limited resolution of the instruments, art...

Black box no more: A cross-sectional multi-disciplinary survey for exploring governance and guiding adoption of AI in medical imaging and radiotherapy in the UK.

International journal of medical informatics
BACKGROUND: Medical Imaging and radiotherapy (MIRT) are at the forefront of artificial intelligence applications. The exponential increase of these applications has made governance frameworks necessary to uphold safe and effective clinical adoption. ...

Surveying the landscape of diagnostic imaging in dentistry's future: Four emerging technologies with promise.

Journal of the American Dental Association (1939)
BACKGROUND: Advances in digital radiography for both intraoral and panoramic imaging and cone-beam computed tomography have led the way to an increase in diagnostic capabilities for the dental care profession. In this article, the authors provide inf...

Hierarchical medical image report adversarial generation with hybrid discriminator.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVES: Generating coherent reports from medical images is an important task for reducing doctors' workload. Unlike traditional image captioning tasks, the task of medical image report generation faces more challenges. Current mode...

Unlocking the Value: Quantifying the Return on Investment of Hospital Artificial Intelligence.

Journal of the American College of Radiology : JACR
PURPOSE: A comprehensive return on investment (ROI) calculator was developed to evaluate the monetary and nonmonetary benefits of an artificial intelligence (AI)-powered radiology diagnostic imaging platform to inform decision makers interested in ad...

Intelligent Integrated System for Fruit Detection Using Multi-UAV Imaging and Deep Learning.

Sensors (Basel, Switzerland)
In the context of Industry 4.0, one of the most significant challenges is enhancing efficiency in sectors like agriculture by using intelligent sensors and advanced computing. Specifically, the task of fruit detection and counting in orchards represe...

Checklist for Reproducibility of Deep Learning in Medical Imaging.

Journal of imaging informatics in medicine
The application of deep learning (DL) in medicine introduces transformative tools with the potential to enhance prognosis, diagnosis, and treatment planning. However, ensuring transparent documentation is essential for researchers to enhance reproduc...

Deep-learning approach to stratified reconstructions of tissue absorption and scattering in time-domain spatial frequency domain imaging.

Journal of biomedical optics
SIGNIFICANCE: The conventional optical properties (OPs) reconstruction in spatial frequency domain (SFD) imaging, like the lookup table (LUT) method, causes OPs aliasing and yields only average OPs without depth resolution. Integrating SFD imaging wi...