AIMC Topic: Image Interpretation, Computer-Assisted

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Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century.

The British journal of radiology
Advances in computing hardware and software platforms have led to the recent resurgence in artificial intelligence (AI) touching almost every aspect of our daily lives by its capability for automating complex tasks or providing superior predictive an...

Artificial intelligence approaches to improve kidney care.

Nature reviews. Nephrology
Artificial intelligence is increasingly being used to improve diagnosis and prognostication for acute and chronic kidney diseases. Studies published in 2019 relied on a variety of available data sources towards this objective, including electronic he...

Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence.

Schizophrenia bulletin
Despite the high level of interest in the use of machine learning (ML) and neuroimaging to detect psychosis at the individual level, the reliability of the findings is unclear due to potential methodological issues that may have inflated the existing...

Artificial Intelligence and Machine Learning in Cardiovascular Imaging.

Methodist DeBakey cardiovascular journal
Cardiovascular disease is the leading cause of mortality in Western countries and leads to a spectrum of complications that can complicate patient management. The emergence of artificial intelligence (AI) has garnered significant interest in many ind...

A brief history of artificial intelligence and robotic surgery in orthopedics & traumatology and future expectations.

Joint diseases and related surgery
Recently, the rate of the production and renewal of information makes it almost impossible to be updated. It is quite difficult to process and interpret large amounts of data by human beings. Unlimited memory capacities, learning abilities, artificia...

Deep Learning for Carotid Plaque Segmentation using a Dilated U-Net Architecture.

Ultrasonic imaging
Carotid plaque segmentation in ultrasound longitudinal B-mode images using deep learning is presented in this work. We report on 101 severely stenotic carotid plaque patients. A standard U-Net is compared with a dilated U-Net architecture in which th...

Recognition of calcifications in thyroid nodules based on attention-gated collaborative supervision network of ultrasound images.

Journal of X-ray science and technology
BACKGROUND: Calcification is an important criterion for classification between benign and malignant thyroid nodules. Deep learning provides an important means for automatic calcification recognition, but it is tedious to annotate pixel-level labels f...

Artificial Intelligence in Cardiovascular Imaging.

Methodist DeBakey cardiovascular journal
The number of cardiovascular imaging studies is growing exponentially, and so is the need to improve clinical workflow efficiency and avoid missed diagnoses. With the availability and use of large datasets, artificial intelligence (AI) has the potent...

Breast Infrared Thermography Segmentation Based on Adaptive Tuning of a Fully Convolutional Network.

Current medical imaging
BACKGROUND: Accurate segmentation of Breast Infrared Thermography is an important step for early detection of breast pathological changes. Automatic segmentation of Breast Infrared Thermography is a very challenging task, as it is difficult to find a...

Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks.

Current medical imaging
BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular h...