AIMC Journal:
Computer methods and programs in biomedicine

Showing 271 to 280 of 844 articles

Automated postural asymmetry assessment in infants neurodevelopmental evaluation using novel video-based features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Neurodevelopmental assessment enables the identification of infant developmental disorders in the first months of life. Thus, the appropriate therapy can be initiated promptly, increasing the chances for correct motor functi...

Deep learning based MRI reconstruction with transformer.

Computer methods and programs in biomedicine
Magnetic resonance imaging (MRI) has become one of the most powerful imaging techniques in medical diagnosis, yet the prolonged scanning time becomes a bottleneck for application. Reconstruction methods based on compress sensing (CS) have made progre...

A deep learning workflow for quantification of micronuclei in DNA damage studies in cultured cancer cell lines: A proof of principle investigation.

Computer methods and programs in biomedicine
The cytokinesis block micronucleus assay is widely used for measuring/scoring/counting micronuclei, a marker of genome instability in cultured and primary cells. Though a gold standard method, this is a laborious and time-consuming process with perso...

Automated location of orofacial landmarks to characterize airway morphology in anaesthesia via deep convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND: A reliable anticipation of a difficult airway may notably enhance safety during anaesthesia. In current practice, clinicians use bedside screenings by manual measurements of patients' morphology.

Local augmentation based consistency learning for semi-supervised pathology image classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Labeling pathology images is often costly and time-consuming, which is quite detrimental for supervised pathology image classification that relies heavily on sufficient labeled data during training. Exploring semi-supervised...

Discriminating and understanding brain states in children with epileptic spasms using deep learning and graph metrics analysis of brain connectivity.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Epilepsy is a brain disorder consisting of abnormal electrical discharges of neurons resulting in epileptic seizures. The nature and spatial distribution of these electrical signals make epilepsy a field for the analysis of ...

Multi-agent medical image segmentation: A survey.

Computer methods and programs in biomedicine
During the last decades, the healthcare area has increasingly relied on medical imaging for the diagnosis of a growing number of pathologies. The different types of medical images are mostly manually processed by human radiologists for diseases detec...

Artificial intelligence based personalized predictive survival among colorectal cancer patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer is a major health concern. It is now the third most common cancer and the fourth leading cause of cancer mortality worldwide. The aim of this study was to evaluate the performance of machine learning algori...

Automatic assessment of pain based on deep learning methods: A systematic review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The automatic assessment of pain is vital in designing optimal pain management interventions focused on reducing suffering and preventing the functional decline of patients. In recent years, there has been a surge in the ado...

PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Open-source deep learning toolkits are one of the driving forces for developing medical image segmentation models that are essential for computer-assisted diagnosis and treatment procedures. Existing toolkits mainly focus on...