AIMC Topic: Diagnostic Imaging

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Basic of machine learning and deep learning in imaging for medical physicists.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
The manuscript aims at providing an overview of the published algorithms/automation tool for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed using the query string to identify the proposed approaches (algorith...

Text-Guided Neural Network Training for Image Recognition in Natural Scenes and Medicine.

IEEE transactions on pattern analysis and machine intelligence
Convolutional neural networks (CNNs) are widely recognized as the foundation for machine vision systems. The conventional rule of teaching CNNs to understand images requires training images with human annotated labels, without any additional instruct...

PyDiNet: Pyramid Dilated Network for medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Medical image segmentation is an important step in many generic applications such as population analysis and, more accessible, can be made into a crucial tool in diagnosis and treatment planning. Previous approaches are based on two main architecture...

Active, continual fine tuning of convolutional neural networks for reducing annotation efforts.

Medical image analysis
The splendid success of convolutional neural networks (CNNs) in computer vision is largely attributable to the availability of massive annotated datasets, such as ImageNet and Places. However, in medical imaging, it is challenging to create such larg...

Do Radiographic Assessments of Periodontal Bone Loss Improve with Deep Learning Methods for Enhanced Image Resolution?

Sensors (Basel, Switzerland)
Resolution plays an essential role in oral imaging for periodontal disease assessment. Nevertheless, due to limitations in acquisition tools, a considerable number of oral examinations have low resolution, making the evaluation of this kind of lesion...

To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines).

European radiology
Artificial intelligence (AI) has made impressive progress over the past few years, including many applications in medical imaging. Numerous commercial solutions based on AI techniques are now available for sale, forcing radiology practices to learn h...

Use of artificial intelligence in the imaging of sarcopenia: A narrative review of current status and perspectives.

Nutrition (Burbank, Los Angeles County, Calif.)
Sarcopenia is a muscle disease which previously was associated only with aging, but in recent days it has been gaining more attention for its predictive value in a vast range of conditions and its potential link with overall health. Up to this point,...

AI applications to medical images: From machine learning to deep learning.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Artificial intelligence (AI) models are playing an increasing role in biomedical research and healthcare services. This review focuses on challenges points to be clarified about how to develop AI applications as clinical decision support sys...

Deep Learning for Biospectroscopy and Biospectral Imaging: State-of-the-Art and Perspectives.

Analytical chemistry
With the advances in instrumentation and sampling techniques, there is an explosive growth of data from molecular and cellular samples. The call to extract more information from the large data sets has greatly challenged the conventional chemometrics...