Digital X-Ray: Page 4

AI cuts time for radiologists reporting fractures on x-rays

A commercially available AI algorithm that can prioritize x-ray exams when it detects fractures yields “tremendous reductions” in report turnaround times.

November 28, 2023

Artificial Intelligence Ai Global Communication Network

3 AI-based technology trends on display at the 2023 RSNA conference

By Vincent Chan

Vincent Chan of Carestream predicts technology trends for AI in digital radiography at RSNA 2023.

November 22, 2023

Hip x-rays help screen for osteoporosis in THA patients

Plain hip x-rays may help screen patients for osteoporosis before they undergo total hip arthroplasty (THA).

November 21, 2023

An example of measurement on plain anterior-posterior x-rays used in the study: canal-bone-ratio CBR-7 cm (Cm/Cc) and CBR-10 cm (Dm/Dc), canal-calcar ratio CCR (Dm/Bm); canal flare index CFI (A/Dm). Image courtesy of Scientific Reports.

AI detects incidental lung nodules on chest x-rays

AI based lesion-detection software used in daily practice can help identify clinically significant incidental lung nodules on chest x-rays

November 16, 2023

A true positive case in a 72-year-old male with a granuloma on chest x-ray after visiting the neurology outpatient clinic for memory disturbance. A small lung nodule was detected in the left-middle to lower lung field by AI software, with an abnormality score of 26%. Co-existing fibrosis was suspected in the apex of bilateral upper lungs, with an abnormality score of 76%. Image courtesy of Scientific Reports.

Julianna Czum talks AI chest radiograph study with AuntMinnie.com

By Amerigo Allegretto

Julianna Czum, MD, spoke with AuntMinnie.com on a study that tested a deep-learning algorithm on triaging chest radiographs.

November 6, 2023

Julianna Czum Interview

AI model predicts scoliosis spinal curve progression

A deep-learning AI model shows promise for predicting spinal curves in individuals with adolescent idiopathic scoliosis.

November 3, 2023

Three regions of interest (ROI) were selected and processed for training from each original radiograph. The leftmost image is the original coronal view radiograph. The original radiograph was passed through the CLAHE algorithm to enhance image brightness and contrast. The three crop boxes outlined by red dotted lines illustrate the three crops generated for model training. Crop 1 selects the ROI for the whole-spine region according to coordinates exported by AlignProCARE. Crops 2 and 3 select the ROIs for the upper and lower end vertebra of the major curvature. All ROIs were subsequently resized into 256 × 256 for Crop 1 and 50 × 50 for Crop 2 and 3. Crop 1 ROI was additionally multiplied by a Gaussian mask to amplify the signal of the vertebrae. Image courtesy of the Global Spine Journal.

Bone health assessed among transgender adults

Puberty suppression treatment in transgender adolescents followed by long-term gender-affirming hormones appears safe for bone health.

November 1, 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.

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.

AI model predicts fracture risk using bone scans

A group in Australia has developed an AI model that shows promise predicting fracture risk in patients based on dual-energy x-ray absorptiometry exams.

October 23, 2023

Visualization of EigenGradCAM (A) and GradCAM results (B) illustrating association between fracture group classification and DXA image features for moderate fracture risk subjects. Given are the three highest confidence images with labels predicted for correct classifications, which ranged from 85% to 92% confidence. Image courtesy of JBMR Plus.

Ultralow-dose chest CT bests x-ray in the emergency department

By Kate Madden Yee

In nontraumatic emergency department patients, ultralow-dose chest CT offers more than twice the detection rate for main diagnoses compared with chest x-ray.

October 19, 2023

Ct Scanner Bore

COVID-19 AI model boosts disease detection by radiologists

An AI algorithm designed to diagnose COVID-19 has been validated in a study by radiologists who interpreted x-rays with and without the model.

October 18, 2023

Results of Grad-CAM and Grad-CAM++ for the deep-learning model: (A) normal, (B) pneumonia, and (C) COVID-19. Left column, original chest x-ray image; middle column, result of Grad-CAM; right column, results of Grad-CAM++ .

Page 4 of 374