Insights into Imaging

Multi-channel deep learning model diagnoses the cause of LVH

A new study sees the development of a fully automatic framework for the diagnosis of the cause of left ventricular hypertrophy (LVH) via cardiac cine images....

Insights into Imaging

2 weeks ago

A novel AI model to distinguish benign from malignant ovarian tumors

The authors of this study developed a CT-based artificial intelligence model with the ability to differentiate between benign and malignant ovarian tumors,...

Insights into Imaging

2 months ago

Structured reporting using an intelligent dialogue system based on speech recognition and NLP

Although structured reporting (SR) is recommended in the field of radiology compared to free-text reporting (FTR), the use of SR still experiences obstacles...

Insights into Imaging

2 months ago

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant...

Insights into Imaging

3 months ago

Covid-19 early detection: Neural Networks vs. Radiologists

The COVID-19 pandemic not only made an impact on the discipline of radiology as a whole but also on how we use specific tools in its detection. This was...

Insights into Imaging

4 months ago

Automated vetting of radiology referrals: exploring NLP and ML approaches

As computed tomography (CT) sees an increase in utilization, inappropriate imaging has been seen as a significant concern; however, manual justification...

Insights into Imaging

4 months ago

T2-weighted MRI-based radiomics discriminati between benign and borderline epithelial ovarian tumors

The authors of this study investigated whether radiomics based on T2-weighted MRI was able to discriminate between benign and borderline epithelial ovarian...

Insights into Imaging

5 months ago

Enhanced CT-based radiomics predicts pathological complete response for advanced adenocarcinoma

This study shows that the combination of CT imaging and clinical factors pre-neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric...

Insights into Imaging

5 months ago

Quality assurance for automatically generated contours with additional deep learning

This study explores the importance of quality assurance when deploying an automatic segmentation model. The authors of this study built a deep-learning model...

Insights into Imaging

5 months ago

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

6 months ago