AIMC Topic: Diagnostic Imaging

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Deep Learning-Based Single-Cell Optical Image Studies.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Optical imaging technology that has the advantages of high sensitivity and cost-effectiveness greatly promotes the progress of nondestructive single-cell studies. Complex cellular image analysis tasks such as three-dimensional reconstruction call for...

Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images.

Communications biology
Retinal detachment can lead to severe visual loss if not treated timely. The early diagnosis of retinal detachment can improve the rate of successful reattachment and the visual results, especially before macular involvement. Manual retinal detachmen...

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

Chest
COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year lo...

Survey on deep learning for pulmonary medical imaging.

Frontiers of medicine
As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and d...

Artificial intelligence in medical imaging.

Magnetic resonance imaging
The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how medical imaging is deployed. Artificial intelligence (AI) is potentially another such developmen...

Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Convolutional Neural Network.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Understanding the intricacies of particle-cell interactions is essential for many applications such as imaging, phototherapy, and drug/gene delivery, because it is the key to accurate control of the particle properties for the improvement of their th...

MedGAN: Medical image translation using GANs.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific arc...

Machine Learning to Quantitate Neutrophil NETosis.

Scientific reports
We introduce machine learning (ML) to perform classification and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate...

Artificial Intelligence in medical imaging practice: looking to the future.

Journal of medical radiation sciences
Artificial intelligence (AI) is heralded as the most disruptive technology to health services in the 21 century. Many commentary articles published in the general public and health domains recognise that medical imaging is at the forefront of these c...