deep learning

Radiologists with and without deep learning–based computer-aided diagnosis

When radiologists encounter pulmonary nodules/masses in computed tomography (CT) images, they diagnose malignancy based on lesion characteristics (e.g.,...

Shoji Kido

2 months ago

Deep learning detection of ACL tear on knee MRI

The purpose of this study was to develop a deep-learning algorithm for tear detection in the anterior cruciate ligament (ACL), subsequently comparing its...

European Radiology

3 months ago

Applications of machine learning for imaging-driven diagnosis of musculoskeletal malignancies

Due to the rare nature of musculoskeletal malignancies and the lack of imaging data associated with this cancer, the authors of this study aimed to...

European Radiology

3 months ago

How well does a 3D convolutional neural network perform in detecting hypoperfusion?

Due to the life-threatening nature of chronic pulmonary embolism (CPE) and how easily it can be misdiagnosed on computed tomography, the authors of this study...

European Radiology Experimental

4 months ago

Clinical applications of AI and radiomics in neuro-oncology

In this educational review, the authors take a comprehensive look at various aspects and applications of artificial intelligence (AI) in the field of...

Insights into Imaging

7 months ago

A deep learning algorithm for VHD diagnosis and evaluation

This study aims to develop and validate a deep learning-based automatic chest radiograph (CXR) cardiovascular border (CB) analysis algorithm (CB_auto) in...

European Radiology

8 months ago

Deep learning radiomics in prediction of NAC response

For breast cancer, the standard of treatment for most patients is neoadjuvant chemotherapy (NAC), but response rates may vary among patients, causing delays...

European Radiology

8 months ago

Deep learning assesses additional radiation dose in overscanning

Following the COVID-19 pandemic, the number of chest CT examinations has dramatically increased, which will undeniably impact public medical exposure....

Yazdan Salimi

8 months ago

Integrated AI model aids ultrasonographers

In this study, the authors aimed to develop an explainable ultrasound (US) computer-assisted diagnostic (CAD) model for suspicious thyroid nodules by...

European Radiology

9 months ago

Saliency-based 3D convolutional neural network for categorising common focal liver lesions on multisequence MRI

We investigated a saliency-based 3D convolutional neural network (CNN) to classify seven categories of common focal liver lesions and validated the model...

Zheng-Han Yang

10 months ago