AI Medical Compendium Journal:
BMC medical imaging

Showing 81 to 90 of 252 articles

Accuracy of deep learning in the differential diagnosis of coronary artery stenosis: a systematic review and meta-analysis.

BMC medical imaging
BACKGROUND: In recent years, as deep learning has received widespread attention in the field of heart disease, some studies have explored the potential of deep learning based on coronary angiography (CAG) or coronary CT angiography (CCTA) images in d...

Predicting invasion in early-stage ground-glass opacity pulmonary adenocarcinoma: a radiomics-based machine learning approach.

BMC medical imaging
BACKGROUND: To design a pulmonary ground-glass nodules (GGN) classification method based on computed tomography (CT) radiomics and machine learning for prediction of invasion in early-stage ground-glass opacity (GGO) pulmonary adenocarcinoma.

Deep learning-based techniques for estimating high-quality full-dose positron emission tomography images from low-dose scans: a systematic review.

BMC medical imaging
This systematic review aimed to evaluate the potential of deep learning algorithms for converting low-dose Positron Emission Tomography (PET) images to full-dose PET images in different body regions. A total of 55 articles published between 2017 and ...

Clinical performance of deep learning-enhanced ultrafast whole-body scintigraphy in patients with suspected malignancy.

BMC medical imaging
BACKGROUND: To evaluate the clinical performance of two deep learning methods, one utilizing real clinical pairs and the other utilizing simulated datasets, in enhancing image quality for two-dimensional (2D) fast whole-body scintigraphy (WBS).

Multimodal medical image fusion based on interval gradients and convolutional neural networks.

BMC medical imaging
Many image fusion methods have been proposed to leverage the advantages of functional and anatomical images while compensating for their shortcomings. These methods integrate functional and anatomical images while presenting physiological and metabol...

Optimized deep CNN for detection and classification of diabetic retinopathy and diabetic macular edema.

BMC medical imaging
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appropriate treatment plan, which ultimately ...

Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.

BMC medical imaging
BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predict...

Deep learning based uterine fibroid detection in ultrasound images.

BMC medical imaging
Uterine fibroids are common benign tumors originating from the uterus's smooth muscle layer, often leading to symptoms such as pelvic pain, and reproductive issues. Early detection is crucial to prevent complications such as infertility or the need f...

An effective no-reference image quality index prediction with a hybrid Artificial Intelligence approach for denoised MRI images.

BMC medical imaging
As the quantity and significance of digital pictures in the medical industry continue to increase, Image Quality Assessment (IQA) has recently become a prevalent subject in the research community. Due to the wide range of distortions that Magnetic Re...