AIMC Topic: Deep Learning

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Super-resolution based Nodule Localization in Thyroid Ultrasound Images through Deep Learning.

Current medical imaging
BACKGROUND: Currently, it is difficult to find a solution to the inverse inappropriate problem, which involves restoring a high-resolution image from a lowresolution image contained within a single image. In nature photography, one can capture a wide...

A fusion of deep neural networks and game theory for retinal disease diagnosis with OCT images.

Journal of X-ray science and technology
Retinal disorders pose a serious threat to world healthcare because they frequently result in visual loss or impairment. For retinal disorders to be diagnosed precisely, treated individually, and detected early, deep learning is a necessary subset of...

A deep learning approach for acute liver failure prediction with combined fully connected and convolutional neural networks.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Acute Liver Failure (ALF) is a critical medical condition with rapid development, often caused by viral infections, hepatotoxic drug abuse, or other severe liver diseases. Timely and accurate prediction of ALF occurrence is clinically cru...

Intelligent deep learning supports biomedical image detection and classification of oral cancer.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Oral cancer is a malignant tumor that usually occurs within the tissues of the mouth. This type of cancer mainly includes tumors in the lining of the mouth, tongue, lips, buccal mucosa and gums. Oral cancer is on the rise globally, especi...

Deep learning-based differentiation of ventricular septal defect from tetralogy of Fallot in fetal echocardiography images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Congenital heart disease (CHD) seriously affects children's health and quality of life, and early detection of CHD can reduce its impact on children's health. Tetralogy of Fallot (TOF) and ventricular septal defect (VSD) are two types of ...

Super-resolution of diffusion-weighted images using space-customized learning model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Diffusion-weighted imaging (DWI) is a noninvasive method used for investigating the microstructural properties of the brain. However, a tradeoff exists between resolution and scanning time in clinical practice. Super-resolution has been e...

Optimizing cardiovascular image segmentation through integrated hierarchical features and attention mechanisms.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Cardiovascular diseases are the top cause of death in China. Manual segmentation of cardiovascular images, prone to errors, demands an automated, rapid, and precise solution for clinical diagnosis.

Applications of deep learning models in precision prediction of survival rates for heart failure patients.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Heart failure poses a significant challenge in the global health domain, and accurate prediction of mortality is crucial for devising effective treatment plans. In this study, we employed a Seq2Seq model from deep learning, integrating 12...

Intelligent quality control of traditional chinese medical tongue diagnosis images based on deep learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Computer-aided tongue and face diagnosis technology can make Traditional Chinese Medicine (TCM) more standardized, objective and quantified. However, many tongue images collected by the instrument may not meet the standard in clinical app...

A novel deep learning technique for medical image analysis using improved optimizer.

Health informatics journal
Application of Convolutional neural network in spectrum of Medical image analysis are providing benchmark outputs which converges the interest of many researchers to explore it in depth. Latest preprocessing technique Real ESRGAN (Enhanced super reso...