AIMC Topic: Humans

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AI in Radiology: Where are we today in Multiple Sclerosis Imaging?

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
BACKGROUND:  MR imaging is an essential component in managing patients with Multiple sclerosis (MS). This holds true for the initial diagnosis as well as for assessing the clinical course of MS. In recent years, a growing number of computer tools wer...

Fully multi-target segmentation for breast ultrasound image based on fully convolutional network.

Medical & biological engineering & computing
Ultrasound image segmentation plays an important role in computer-aided diagnosis of breast cancer. Existing approaches focused on extracting the tumor tissue to characterize the tumor class. However, other tissues are also helpful for providing the ...

Feasibility and analysis of CNN-based candidate beam generation for robotic radiosurgery.

Medical physics
PURPOSE: Robotic radiosurgery offers the flexibility of a robotic arm to enable high conformity to the target and a steep dose gradient. However, treatment planning becomes a computationally challenging task as the search space for potential beam dir...

Deep convolutional neural network-based anomaly detection for organ classification in gastric X-ray examination.

Computers in biology and medicine
AIM: The aim of this study was to determine whether our deep convolutional neural network-based anomaly detection model can distinguish differences in esophagus images and stomach images obtained from gastric X-ray examinations.

Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.

Emergency radiology
PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment ...

The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Emergency radiology
Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at all. The use of AI appears to show significant promise in ER triage in the present. We briefly disc...

A Method for Sensor-Based Activity Recognition in Missing Data Scenario.

Sensors (Basel, Switzerland)
Sensor-based human activity recognition has various applications in the arena of healthcare, elderly smart-home, sports, etc. There are numerous works in this field-to recognize various human activities from sensor data. However, those works are base...

Using diffusion tensor imaging to detect cortical changes in fronto-temporal dementia subtypes.

Scientific reports
Fronto-temporal dementia (FTD) is a common type of presenile dementia, characterized by a heterogeneous clinical presentation that includes three main subtypes: behavioural-variant FTD, non-fluent/agrammatic variant primary progressive aphasia and se...