AI Medical Compendium Journal:
Journal of imaging informatics in medicine

Showing 91 to 100 of 183 articles

Iterative Motion Correction Technique with Deep Learning Reconstruction for Brain MRI: A Volunteer and Patient Study.

Journal of imaging informatics in medicine
The aim of this study was to investigate the effect of iterative motion correction (IMC) on reducing artifacts in brain magnetic resonance imaging (MRI) with deep learning reconstruction (DLR). The study included 10 volunteers (between September 2023...

GLGFormer: Global Local Guidance Network for Mucosal Lesion Segmentation in Gastrointestinal Endoscopy Images.

Journal of imaging informatics in medicine
Automatic mucosal lesion segmentation is a critical component in computer-aided clinical support systems for endoscopic image analysis. Image segmentation networks currently rely mainly on convolutional neural networks (CNNs) and Transformers, which ...

LightGBM is an Effective Predictive Model for Postoperative Complications in Gastric Cancer: A Study Integrating Radiomics with Ensemble Learning.

Journal of imaging informatics in medicine
Postoperative complications of radical gastrectomy seriously affect postoperative recovery and require accurate risk prediction. Therefore, this study aimed to develop a prediction model specifically tailored to guide perioperative clinical decision-...

Detection and Localization of Spine Disorders from Plain Radiography.

Journal of imaging informatics in medicine
Spine disorders can cause severe functional limitations, including back pain, decreased pulmonary function, and increased mortality risk. Plain radiography is the first-line imaging modality to diagnose suspected spine disorders. Nevertheless, radiog...

ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging.

Journal of imaging informatics in medicine
As the adoption of artificial intelligence (AI) systems in radiology grows, the increase in demand for greater bandwidth and computational resources can lead to greater infrastructural costs for healthcare providers and AI vendors. To that end, we de...

Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning.

Journal of imaging informatics in medicine
Early and accurate detection of cervical lymph nodes is essential for the optimal management and staging of patients with head and neck malignancies. Pilot studies have demonstrated the potential for radiomic and artificial intelligence (AI) approach...

Artificial Intelligence for Otosclerosis Detection: A Pilot Study.

Journal of imaging informatics in medicine
The gold standard for otosclerosis diagnosis, aside from surgery, is high-resolution temporal bone computed tomography (TBCT), but it can be compromised by the small size of the lesions. Many artificial intelligence (AI) algorithms exist, but they ar...

Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms.

Journal of imaging informatics in medicine
Breast cancer is the most common cancer in women. Ultrasound is one of the most used techniques for diagnosis, but an expert in the field is necessary to interpret the test. Computer-aided diagnosis (CAD) systems aim to help physicians during this pr...

Removing Adversarial Noise in X-ray Images via Total Variation Minimization and Patch-Based Regularization for Robust Deep Learning-based Diagnosis.

Journal of imaging informatics in medicine
Deep learning has significantly advanced the field of radiology-based disease diagnosis, offering enhanced accuracy and efficiency in detecting various medical conditions through the analysis of complex medical images such as X-rays. This technology'...

Evolutionary Strategies AI Addresses Multiple Technical Challenges in Deep Learning Deployment: Proof-of-Principle Demonstration for Neuroblastoma Brain Metastasis Detection.

Journal of imaging informatics in medicine
Two significant obstacles hinder the advancement of Radiology AI. The first is the challenge of overfitting, where small training data sets can result in unreliable outcomes. The second challenge is the need for more generalizability, the lack of whi...