machine learning

Automatic segmentation and classification of breast lesions through identification of informative multiparametric PET/MRI features

The authors of this study recognized the potential of multiparametric positron emission tomography/magnetic resonance imaging (mpPET/MRI) for detecting and...

European Radiology Experimental

3 years ago

AI guru gives a glimpse into the future of radiology with AI

With the advent of Artificial Intelligence, new opportunities will arise for radiologists if they remain focused and critical, ‘rock star of the digital...

Melisande Rouger

3 years ago

Artificial intelligence in abdominal imaging at the 30th annual meeting of ESGAR 2019 in Rome, Italy

This week, the European Society of Gastrointestinal and Abdominal Radiology (ESGAR) will head to Rome, Italy, where they will host the ESGAR 2019 30th Annual...

ESR

3 years ago

Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs

In this study, we developed the DCNN not only for the automated detection of hip fractures on frontal pelvic radiographs but also to offer visualization of...

Chien-Hung Liao, Chi-Tung Cheng

4 years ago

Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT

Deep learning reconstruction (DLR) is a novel method of reconstruction that introduces deep convolutional neural networks into the reconstruction flow. The...

European Radiology

4 years ago

Using machine learning to predict cervical lymph node metastasis on dual-energy CT

In this article, we extracted “hand-crafted” radiomic features from dual-energy CT (DECT) virtual monochromatic images (VMIs) reconstructed at different...

Reza Forghani

4 years ago

How machine learning-based high-dimensional CT texture analysis is influenced by segmentation margin

Radiomic workflows include various challenging steps. One of the most demanding steps in radiomics is the segmentation process. Particularly for the renal...

Burak Kocak

4 years ago

Strategic research agenda for biomedical imaging

Over the last years, medicine has been moving further towards providing a more tailored, patient-centric approach by taking into account as much information...

Daniel Pinto dos Santos

4 years ago

Applying 3D CNN to CTA source images to detect ischemic stroke

In this study, the authors investigated how feasible it was to use 3D convolutional neural networks (CNN) to detect ischemic stroke from computed tomography...

European Radiology Experimental

4 years ago

Using deep learning to detect and segment meningiomas

These days, selling a medical product or software solution without bringing up ‘artificial intelligence’ seems to be an almost impossible task. Hence, a...

Kai Roman Laukamp

4 years ago