AI Medical Compendium Journal:
Current medical imaging

Showing 81 to 90 of 127 articles

Distinguishing Intramedullary Spinal Cord Neoplasms from Non-Neoplastic Conditions by Analyzing the Classic Signs on MRI in the Era of AI.

Current medical imaging
Intramedullary lesions can be challenging to diagnose, given the wide range of possible pathologies. Each lesion has unique clinical and imaging features, which are best evaluated using magnetic resonance imaging. Radiological imaging is unique with ...

Brain Tumor Detection Using Machine Learning and Deep Learning: A Review.

Current medical imaging
According to the International Agency for Research on Cancer (IARC), the mortality rate due to brain tumors is 76%. It is required to detect the brain tumors as early as possible and to provide the patient with the required treatment to avoid any fat...

A Novel Multicolor-thresholding Auto-detection Method to Detect the Location and Severity of Inflammation in Confirmed SARS-COV-2 Cases using Chest X-Ray Images.

Current medical imaging
OBJECTIVES: Since late 2019, Coronavirus Disease 2019 (COVID-19) has spread around the world. It has been determined that the disease is very contagious and can cause Acute Respiratory Distress (ARD). Medical imaging has the potential to help identif...

Advanced Deep Learning Algorithms for Infectious Disease Modeling Using Clinical Data: A Case Study on COVID-19.

Current medical imaging
BACKGROUND: Dealing with the COVID-19 pandemic has been one of the most important objectives of many countries.Intently observing the growth dynamics of the cases is one way to accomplish the solution for the pandemic.

Quantitative Comparisons of Deep-learning-based and Atlas-based Auto- segmentation of the Intermediate Risk Clinical Target Volume for Nasopharyngeal Carcinoma.

Current medical imaging
BACKGROUND: Manual segment target volumes were time-consuming and inter-observer variability couldn't be avoided. With the development of computer science, auto-segmentation had the potential to solve this problem.

Lung Nodule Detectability of Artificial Intelligence-assisted CT Image Reading in Lung Cancer Screening.

Current medical imaging
BACKGROUND: Artificial Intelligence (AI)-based automatic lung nodule detection system improves the detection rate of nodules. It is important to evaluate the clinical value of the AI system by comparing AI-assisted nodule detection with actual radiol...

Robust Engineering-based Unified Biomedical Imaging Framework for Liver Tumor Segmentation.

Current medical imaging
BACKGROUND: Computer vision in general and semantic segmentation has experienced many achievements in recent years. Consequently, the emergence of medical imaging has provided new opportunities for conducting artificial intelligence research. Since c...

A Survey on Machine Learning Based Medical Assistive Systems in Current Oncological Sciences.

Current medical imaging
BACKGROUND: Cancer is one of the life-threatening diseases which is affecting a large number of population worldwide. Cancer cells multiply inside the body without showing much symptoms on the surface of the skin, thereby making it difficult to predi...

An Efficient Method for Coronavirus Detection Through X-rays Using Deep Neural Network.

Current medical imaging
BACKGROUND: Coronavirus (COVID-19) is a group of infectious diseases caused by related viruses called coronaviruses. In humans, the seriousness of infection caused by a coronavirus in the respiratory tract can vary from mild to lethal. A serious illn...

Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A Review.

Current medical imaging
BACKGROUND: This paper provides a systematic review of the application of Artificial Intelligence (AI) in the form of Machine Learning (ML) and Deep Learning (DL) techniques in fighting against the effects of novel coronavirus disease (COVID-19).