AIMC Topic: Deep Learning

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Deep learning enabled brain shunt valve identification using mobile phones.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate information concerning implanted medical devices prior to a Magnetic resonance imaging (MRI) examination is crucial to assure safety of the patient and to address MRI induced unintended changes in device settings. T...

Detection of fraud in ginger powder using an automatic sorting system based on image processing technique and deep learning.

Computers in biology and medicine
Ginger is a well-known product in the food and pharmaceutical industries. Ginger is one of the spices which are adulterated for economic gain. The lack of marketability of grade 3 chickpeas (small and broken chickpeas) and their very low price have m...

Deep learning-based forward and cross-scatter correction in dual-source CT.

Medical physics
PURPOSE: Dual-source computed tomography (DSCT) uses two source-detector pairs offset by about 90°. In addition to the well-known forward scatter, a special issue in DSCT is cross-scattered radiation from X-ray tube A detected in the detector of syst...

Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing.

Sensors (Basel, Switzerland)
The demand for the sensor-based detection of camouflage objects widely exists in biological research, remote sensing, and military applications. However, the performance of traditional object detection algorithms is limited, as they are incapable of ...

Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer.

Scientific reports
The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selection method suitable for gene selection. Our novel deep learning model includes an additional feature-s...

Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement.

BMC medical imaging
BACKGROUND: Accurate measurement of hemorrhage volume is critical for both the prediction of prognosis and the selection of appropriate clinical treatment after spontaneous intracerebral hemorrhage (ICH). This study aimed to evaluate the performance ...

An artifıcial ıntelligence approach to automatic tooth detection and numbering in panoramic radiographs.

BMC medical imaging
BACKGROUND: Panoramic radiography is an imaging method for displaying maxillary and mandibular teeth together with their supporting structures. Panoramic radiography is frequently used in dental imaging due to its relatively low radiation dose, short...

A deep learning method for single-trial EEG classification in RSVP task based on spatiotemporal features of ERPs.

Journal of neural engineering
. Single-trial electroencephalography (EEG) classification is of great importance in the rapid serial visual presentation (RSVP) task. Convolutional neural networks (CNNs), as one of the mainstream deep learning methods, have been proven to be effect...

Unveiling functions of the visual cortex using task-specific deep neural networks.

PLoS computational biology
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We r...

Demystifying artificial intelligence and deep learning in dentistry.

Brazilian oral research
Artificial intelligence (AI) is a general term used to describe the development of computer systems which can perform tasks that normally require human cognition. Machine learning (ML) is one subfield of AI, where computers learn rules from data, cap...