AI Medical Compendium Journal:
Journal of ultrasound

Showing 1 to 9 of 9 articles

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

Journal of ultrasound
PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting to Pediatric Emergency Departments (EDs). These fractures are treated conservatively or surgically depending on deformity severity. Radiographs are t...

An overview of the use of cutting-edge artificial intelligence (AI) modeling to produce synthetic medical data (SMD) in decentralized clinical machine learning (ML) for ovarian cancer(OC) and ovarian lymphoma(OL).

Journal of ultrasound
AIM: o point out how novel analysis tools of AI can make sense of the data acquired during OL and OC diagnosis and treatment in an effort to help improve and standardize the patient pathway for these disease.

TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.

Journal of ultrasound
PURPOSE: The thyroid imaging reporting and data system (TIRADS) was developed as a standard global term to describe thyroid nodule risk features, aiming to address issues such as variability and low reproducibility in nodule feature detection and int...

A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images.

Journal of ultrasound
Ultrasonography is widely used to screen thyroid tumors because it is safe, easy to use, and low-cost. However, it is simultaneously affected by speckle noise and other artifacts, so early detection of thyroid abnormalities becomes difficult for the ...

Objective assessment of segmentation models for thyroid ultrasound images.

Journal of ultrasound
Ultrasound features related to thyroid lesions structure, shape, volume, and margins are considered to determine cancer risk. Automatic segmentation of the thyroid lesion would allow the sonographic features to be estimated. On the basis of clinical ...

Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics.

Journal of ultrasound
AIMS: We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.

Deep learning applied to breast imaging classification and segmentation with human expert intervention.

Journal of ultrasound
PURPOSE: Automatic classification and segmentation of tumors in breast ultrasound images enables better diagnosis and planning treatment strategies for breast cancer patients.

Inferior epigastric artery pseudoaneurysm secondary to port placement during a robot-assisted laparoscopic radical cystectomy.

Journal of ultrasound
Pseudoaneurysm occurs when the artery wall is damaged and the blood is contained by the surrounding tissues with the eventual formation of a fibrous sac communicating with the artery. We report a case of a 74-year-old man with inferior epigastric art...