AI Medical Compendium Journal:
Journal of imaging informatics in medicine

Showing 131 to 140 of 183 articles

An Automated Multi-scale Feature Fusion Network for Spine Fracture Segmentation Using Computed Tomography Images.

Journal of imaging informatics in medicine
Spine fractures represent a critical health concern with far-reaching implications for patient care and clinical decision-making. Accurate segmentation of spine fractures from medical images is a crucial task due to its location, shape, type, and sev...

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Journal of imaging informatics in medicine
Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated an automated deep learning (DL)-based framework that segments and classifies uptake on PSMA PET/CT. ...

Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet.

Journal of imaging informatics in medicine
Capsule endoscopy (CE) is non-invasive and painless during gastrointestinal examination. However, capsule endoscopy can increase the workload of image reviewing for clinicians, making it prone to missed and misdiagnosed diagnoses. Current researches ...

A Comparative Analysis of Deep Learning-Based Approaches for Classifying Dental Implants Decision Support System.

Journal of imaging informatics in medicine
This study aims to provide an effective solution for the autonomous identification of dental implant brands through a deep learning-based computer diagnostic system. It also seeks to ascertain the system's potential in clinical practices and to offer...

A Guideline for Open-Source Tools to Make Medical Imaging Data Ready for Artificial Intelligence Applications: A Society of Imaging Informatics in Medicine (SIIM) Survey.

Journal of imaging informatics in medicine
In recent years, the role of Artificial Intelligence (AI) in medical imaging has become increasingly prominent, with the majority of AI applications approved by the FDA being in imaging and radiology in 2023. The surge in AI model development to tack...

Deep Convolutional Neural Network for Dedicated Regions-of-Interest Based Multi-Parameter Quantitative Ultrashort Echo Time (UTE) Magnetic Resonance Imaging of the Knee Joint.

Journal of imaging informatics in medicine
We proposed an end-to-end deep learning convolutional neural network (DCNN) for region-of-interest based multi-parameter quantification (RMQ-Net) to accelerate quantitative ultrashort echo time (UTE) MRI of the knee joint with automatic multi-tissue ...

Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.

Journal of imaging informatics in medicine
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness. Diagnosing the malignant lung nodules in its initial stage significantly enhances the recovery and survival ra...

DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus.

Journal of imaging informatics in medicine
Depth of focus (DOF) is defined as the axial range in which the specimen stage moves without losing focus while the imaging apparatus remains stable. It may not be possible to capture an image that includes the entire specimen in focus due to the nar...

Active Learning in Brain Tumor Segmentation with Uncertainty Sampling and Annotation Redundancy Restriction.

Journal of imaging informatics in medicine
Deep learning models have demonstrated great potential in medical imaging but are limited by the expensive, large volume of annotations required. To address this, we compared different active learning strategies by training models on subsets of the m...

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.

Journal of imaging informatics in medicine
This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in computed tomography (CT) for hepatic lesion d...