machine learning

Deep Learning–driven classification of external DICOM studies for PACS archiving

The authors of this study used a deep learning-based approach, MOdality Mapping and Orchestration (MOMO), to deal with potential issues that are caused when...

European Radiology

2 weeks ago

AI for radiological paediatric fracture assessment

Fractures in children are common, sometimes subtle and can signify underlying child abuse. They present unique challenges, given the different appearances of...

Susan Shelmerdine

3 weeks ago

MRI-based radiomics to predict response in locally advanced rectal cancer

The study aimed to implement and externally validate an MRI-based radiomics pipeline in order to predict the response to treatment of locally advanced rectal...

European Radiology Experimental

2 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

Radiomic assessment of oesophageal adenocarcinoma

The use of radiomic models offers a possible way to improve oesophageal adenocarcinoma assessment through quantitative image analysis, but model selection...

Insights into Imaging

3 months ago

Single-center versus multi-center biparametric MRI radiomics approach

In this study, the authors’ aim was to investigate a previously developed radiomics-based biparametric magnetic resonance imaging (bpMRI) approach used...

Insights into Imaging

6 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

Can machine learning predict the WHO/ISUP nuclear grade of clear cell renal cell carcinomas?

In this retrospective study, the authors investigated if radiomics features extracted from nephrographic-phase (NP) CT images combined with...

Insights into Imaging

7 months ago

Measuring bias when using cross-validation in radiomics

Radiomics studies often perform a feature selection step to remove redundant and irrelevant features from the generic features extracted from radiological...

Aydin Demircioğlu

10 months ago

Artificial neural network detects contrast phase in MDCT

Automated extraction of novel biomarkers from routine imaging examinations, e.g., opportunistic CT, is a promising opportunity to extend current screening...

Sebastian Rühling

10 months ago