Imaging Informatics: Page 47

CT radiomics help characterize retroperitoneal sarcomas

By Kate Madden Yee

CT radiomics can help clinicians predict the histological type and grade of retroperitoneal sarcomas, a recently published study has found.

November 2, 2023

AI boosts radiologist perception training

A team in Europe has launched a novel web application to help radiology trainees gain skills in detecting lung nodules on chest x-rays.

October 31, 2023

Screenshots of the imaging viewer interface before (a-b) and after (c-d) having clicked “Review placed markers.” The “Case assessment widget” has been magnified in (b,d). One marker was incorrectly placed (c), which is signified with a red cross. One nodule was not identified (c) and was highlighted by a yellow circle through the mouse over function in the “List of synthetic lesions.” Image courtesy of the British Journal of Radiology.

Abdominal fat CT radiomics help predict liver cancer recurrence

By Kate Madden Yee

CT radiomics features identified from abdominal fat and muscle tissue can help predict early recurrence of liver cancer after surgery, researchers have found.

October 31, 2023

Fat Tissue Adipocytes 400

3D imaging modeling cost-effective for pediatric surgery

By Amerigo Allegretto

3D anatomical modeling using advanced imaging software can be cost-effective in planning pediatric surgeries.

October 31, 2023

Virtual Reality Brain Surgeons 400

AI may boost arthroplasty imaging research

Researchers at the Mayo Clinic have taken a first step in using AI to automatically classify and organize shoulder x-rays on a large scale.

October 27, 2023

ChatGPT may help educate interventional radiology patients

ChatGPT is a relatively safe and accurate tool for patient education in interventional radiology.

October 26, 2023

AI model shows promise for interpreting follow-up chest x-rays

A group in Seoul, South Korea, has developed an AI model that could help reduce radiology workflows by identifying “no changes” in follow-up chest x‑rays.

October 24, 2023

Example of triage of no change in a pair of chest radiographs in the emergency department. (A) Baseline posteroanterior chest radiograph in a 63-year-old female patient shows a small amount of left (L) pleural effusion and partial atelectasis of the right middle lobe. (B) Follow-up posteroanterior chest radiograph obtained in the same patient 1 day later shows no significant change. (C) Gradient-weighted class activation map shows the algorithm determined no change in the image pair, without relevant highlighting, as the highlighted area is located over the gastroesophageal junction. Image courtesy of Radiology.

Deep-learning method using ultrasound predicts fetal birth weight

By Amerigo Allegretto

A novel deep-learning method using ultrasound videos predicts fetal birth weight.

October 23, 2023

Fetal Ultrasound 400

ChatGPT in radiology: Evidence so far

Most published articles testing ChatGPT in radiology show impressive performance, with those noting its limitations opening opportunities to improve the tool itself.

October 23, 2023

ChatGPT, Bard similar in suggesting best method for urologic imaging

By Amerigo Allegretto

ChatGPT and Bard are similar in suggesting the most appropriate urologic imaging method based on American College of Radiology criteria.

October 23, 2023

Artificial Intelligence Ai Abstract Futuristic 400 (1)

Is ChatGPT too ‘smart’ for its own good?

ChatGPT shows promise in answering questions by radiology patients, yet the complexity of its responses may complicate its use as a patient education tool.

October 20, 2023

Venture capital funding will prompt radiology AI clearances

Based on recent correlations between venture capital funding and FDA clearances, FDA-cleared radiology AI offerings are expected to increase substantially.

October 18, 2023

Artificial Intelligence Ai

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