AIMC Topic: Deep Learning

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Deep learning for emergency ascites diagnosis using ultrasonography images.

Journal of applied clinical medical physics
PURPOSE: The detection of abdominal free fluid or hemoperitoneum can provide critical information for clinical diagnosis and treatment, particularly in emergencies. This study investigates the use of deep learning (DL) for identifying peritoneal free...

Novel COVID-19 Diagnosis Delivery App Using Computed Tomography Images Analyzed with Saliency-Preprocessing and Deep Learning.

Tomography (Ann Arbor, Mich.)
This app project was aimed to remotely deliver diagnoses and disease-progression information to COVID-19 patients to help minimize risk during this and future pandemics. Data collected from chest computed tomography (CT) scans of COVID-19-infected pa...

Diagnostic advantage of thin slice 2D MRI and multiplanar reconstruction of the knee joint using deep learning based denoising approach.

Scientific reports
The purpose of this study is to evaluate whether thin-slice high-resolution 2D fat-suppressed proton density-weighted image of the knee joint using denoising approach with deep learning-based reconstruction (dDLR) with MPR is more useful than 3D FS-P...

Multimodal deep learning for Alzheimer's disease dementia assessment.

Nature communications
Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we...

On the role of deep learning model complexity in adversarial robustness for medical images.

BMC medical informatics and decision making
BACKGROUND: Deep learning (DL) models are highly vulnerable to adversarial attacks for medical image classification. An adversary could modify the input data in imperceptible ways such that a model could be tricked to predict, say, an image that actu...

High frame rate (∼3 Hz) circular photoacoustic tomography using single-element ultrasound transducer aided with deep learning.

Journal of biomedical optics
SIGNIFICANCE: In circular scanning photoacoustic tomography (PAT), it takes several minutes to generate an image of acceptable quality, especially with a single-element ultrasound transducer (UST). The imaging speed can be enhanced by faster scanning...

VCNet: Hybrid Deep Learning Model for Detection and Classification of Lung Carcinoma Using Chest Radiographs.

Frontiers in public health
Detection of malignant lung nodules from Computed Tomography (CT) images is a significant task for radiologists. But, it is time-consuming in nature. Despite numerous breakthroughs in studies on the application of deep learning models for the identif...

Pooling Learning: From "Invariable" to "Variable".

BioMed research international
Deep learning has become a research hotspot in multimedia, especially in the field of image processing. Pooling operation is an important operation in deep learning. Pooling operation can reduce the feature dimension, the number of parameters, the co...

College Organizational Innovation Performance-Oriented Internal Mechanism Analysis Using Lightweight Deep Learning under Health Psychology.

Computational intelligence and neuroscience
The purpose is to improve employees' initiative and innovation performance and further improve the overall organizational efficiency of colleges. From the perspective of health psychology, this work analyzes the internal mechanism between leadership ...