AI Medical Compendium Journal:
Medical & biological engineering & computing

Showing 111 to 120 of 330 articles

SALW-Net: a lightweight convolutional neural network based on self-adjusting loss function for spine MR image segmentation.

Medical & biological engineering & computing
Segmentation of intervertebral discs and vertebrae from spine magnetic resonance (MR) images is essential to aid diagnosis algorithms for lumbar disc herniation. Convolutional neural networks (CNN) are effective methods, but often require high comput...

Improved bioimpedance spectroscopy tissue classification through data augmentation from generative adversarial networks.

Medical & biological engineering & computing
Bioimpedance spectroscopy is a tissue classification technique with many clinical applications. Similarly to other data-driven methods, it requires large amounts of data to accurately distinguish similar classes of tissue. Classifiers trained on smal...

Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images.

Medical & biological engineering & computing
Knowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, severa...

Generative adversarial network: a statistical-based deep learning paradigm to improve detecting breast cancer in thermograms.

Medical & biological engineering & computing
Thermography, as a harmless modality, thanks to its low equipment complexity in parallel with quick and cheap access, has been able to come up as a method with significant potential in the diagnosis of some cancers in recent years. However, the compl...

Design and analysis of a compatible exoskeleton rehabilitation robot system based on upper limb movement mechanism.

Medical & biological engineering & computing
Rehabilitation robots are used to promote structural and functional recovery of the nervous system with repetitive, task-oriented training and have been gradually applied to clinical rehabilitation training. This paper proposes an upper limb exoskele...

Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity.

Medical & biological engineering & computing
Retinal vascular tortuosity is an excessive bending and twisting of the blood vessels in the retina that is associated with numerous health conditions. We propose a novel methodology for the automated assessment of the retinal vascular tortuosity fro...

Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction.

Medical & biological engineering & computing
In recent years, the growing awareness of public health has brought attention to low-dose computed tomography (LDCT) scans. However, the CT image generated in this way contains a lot of noise or artifacts, which make increasing researchers to investi...

Space-CNN: a decision classification method based on EEG signals from different brain regions.

Medical & biological engineering & computing
Decision-making plays a critical role in an individual's interpersonal interactions and cognitive processes. Due to the issue of strong subjectivity in the classification research of art design decisions, we utilize the relatively objective electroen...

DBPNDNet: dual-branch networks using 3DCNN toward pulmonary nodule detection.

Medical & biological engineering & computing
With the advancement of artificial intelligence, CNNs have been successfully introduced into the discipline of medical data analyzing. Clinically, automatic pulmonary nodules detection remains an intractable issue since those nodules existing in the ...

Deep learning-based 3D brain multimodal medical image registration.

Medical & biological engineering & computing
Medical image registration is a critical preprocessing step in medical image analysis. While traditional medical image registration techniques have matured, their registration speed and accuracy still fall short of clinical requirements. In this pape...