AIMC Topic: Diagnostic Imaging
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A Machine Learning-Based Screening Test for Sarcopenic Dysphagia Using Image Recognition.
Nutrients
Nov 10, 2021
BACKGROUND: Sarcopenic dysphagia, a swallowing disorder caused by sarcopenia, is prevalent in older patients and can cause malnutrition and aspiration pneumonia. This study aimed to develop a simple screening test using image recognition with a low r...
What will we ask to artificial intelligence for cardiovascular medicine in the next decade?
Minerva cardiology and angiology
Oct 29, 2021
Artificial intelligence (AI) comprises a wide range of technologies and methods with heterogeneous degrees of complexity, applications, and abilities. In the cardiovascular field, AI holds the potential to fulfil many unsolved challenges, eventually ...
A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Oct 27, 2021
Photoacoustic imaging (PAI) has attracted great attention as a medical imaging method. Typically, photoacoustic (PA) images are reconstructed via beamforming, but many factors still hinder the beamforming techniques in reconstructing optimal images i...
Dynamic Learning Rate in Deep CNN Model for Metastasis Detection and Classification of Histopathology Images.
Computational and mathematical methods in medicine
Oct 26, 2021
Diagnosis of different breast cancer stages using histopathology whole slide images (WSI) is the gold standard in determining the grade of tissue metastasis. Computer-aided diagnosis (CAD) assists medical experts as a second opinion tool in early det...
A weakly supervised deep learning approach for label-free imaging flow-cytometry-based blood diagnostics.
Cell reports methods
Oct 25, 2021
The application of machine learning approaches to imaging flow cytometry (IFC) data has the potential to transform the diagnosis of hematological diseases. However, the need for manually labeled single-cell images for machine learning model training ...
Medical Augmentation (Med-Aug) for Optimal Data Augmentation in Medical Deep Learning Networks.
Sensors (Basel, Switzerland)
Oct 22, 2021
Deep learning (DL) algorithms have become an increasingly popular choice for image classification and segmentation tasks; however, their range of applications can be limited. Their limitation stems from them requiring ample data to achieve high perfo...
A muggles guide to deep learning wizardry.
Radiography (London, England : 1995)
Oct 21, 2021
OBJECTIVES: Growing interest in the applications of artificial intelligence (AI) and, in particular, deep learning (DL) in nuclear medicine and radiology partitions the professional community. At one end of the spectrum are our expert DL wizards deve...
Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review.
BMJ open
Oct 20, 2021
INTRODUCTION: The application of artificial intelligence (AI) technologies as a diagnostic aid in healthcare is increasing. Benefits include applications to improve health systems, such as rapid and accurate interpretation of medical images. This may...
Rapid Quality Assessment of Nonrigid Image Registration Based on Supervised Learning.
Journal of digital imaging
Oct 13, 2021
When preprocedural images are overlaid on intraprocedural images, interventional procedures benefit in that more structures are revealed in intraprocedural imaging. However, image artifacts, respiratory motion, and challenging scenarios could limit t...
Accelerating Development and Clinical Deployment of Diagnostic Imaging Artificial Intelligence.
Journal of the American College of Radiology : JACR
Oct 11, 2021
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