Insights into Imaging

Utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics

The aim of this study was to provide an updated systematic review of radiomics in osteosarcoma, utilizing various databases such as PubMed, Embase, China...

Insights into Imaging

2 weeks ago

Detecting dysthyroid optic neropathy using radiomics analysis of the optic nerve

Because the early detection of dysthyroid optic neuropathy (DON) is of the utmost importance for clinical decision-making, the authors of this study aimed to...

Insights into Imaging

3 weeks ago

Application of deep learning reconstruction in the diagnosis of renal calculi

In this study, the authors evaluated the diagnostic capability, image quality, and radiation dose of abdominal ultra-low-dose CT (ULDCT) with deep learning...

Insights into Imaging

2 months ago

Reproducibility of AI models in head CT

The authors of this study reviewed research on AI algorithms relating to computed tomography (CT) of the head in order to verify to what degree it is true...

Insights into Imaging

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

7 months ago

Radiomic features of breast parenchyma

The object of this study was to assess the similarities and differences of radiomics features on full field digital mammography (FFDM) in FOR PROCESSING and...

Insights into Imaging

9 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

9 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

11 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

11 months ago

Misunderstandings on equitable and inequitable biases in machine learning

In this reply to a ‘Letter to the editor‘, the authors seek to correct a few misunderstandings relating to equitable and inequitable biases in...

Insights into Imaging

12 months ago