AIMC Topic: Diagnostic Imaging

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Radiomics: from qualitative to quantitative imaging.

The British journal of radiology
Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes. As a result of advances in both computational hardware and...

Preparing Medical Imaging Data for Machine Learning.

Radiology
Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The potential applications are vast and include the entirety of the medical imaging life cycle from image creation to diagnosis to outcome prediction. The chief...

[Methods of artificial intelligence and their application in imaging diagnostics].

Magyar onkologia
Artificial intelligence is a dynamically evolving methodology and, due to its large number of methods, its appearance becomes more important not only in industry but also in all disciplines. Diagnostic instrument manufacturers have realized relativel...

Unsupervised Domain Adaptation to Classify Medical Images Using Zero-Bias Convolutional Auto-Encoders and Context-Based Feature Augmentation.

IEEE transactions on medical imaging
The accuracy and robustness of image classification with supervised deep learning are dependent on the availability of large-scale labelled training data. In medical imaging, these large labelled datasets are sparse, mainly related to the complexity ...

Artificial Intelligence in Radiology Residency Training.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) is an emerging technology that brings a wide array of new tools to the field of radiology. AI will certainly have an impact on the day-to-day work of radiologists in the coming decades, thus training programs must prepare...

From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.

Seminars in musculoskeletal radiology
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...

Quantification in Musculoskeletal Imaging Using Computational Analysis and Machine Learning: Segmentation and Radiomics.

Seminars in musculoskeletal radiology
Although still limited in clinical practice, quantitative analysis is expected to increase the value of musculoskeletal (MSK) imaging. Segmentation aims at isolating the tissues and/or regions of interest in the image and is crucial to the extraction...

Pattern Recognition in Musculoskeletal Imaging Using Artificial Intelligence.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) has the potential to affect every step of the radiology workflow, but the AI application that has received the most press in recent years is image interpretation, with numerous articles describing how AI can help detect a...

Artificial Intelligence Explained for Nonexperts.

Seminars in musculoskeletal radiology
Artificial intelligence (AI) has made stunning progress in the last decade, made possible largely due to the advances in training deep neural networks with large data sets. Many of these solutions, initially developed for natural images, speech, or t...