AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 3621 to 3630 of 10288 articles

Federated Learning: A Cross-Institutional Feasibility Study of Deep Learning Based Intracranial Tumor Delineation Framework for Stereotactic Radiosurgery.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning-based segmentation algorithms usually required large or multi-institute data sets to improve the performance and ability of generalization. However, protecting patient privacy is a key concern in the multi-institutional stud...

Automated chronic wounds medical assessment and tracking framework based on deep learning.

Computers in biology and medicine
Chronic wounds are a latent health problem worldwide, due to high incidence of diseases such as diabetes and Hansen. Typically, wound evolution is tracked by medical staff through visual inspection, which becomes problematic for patients in rural are...

FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines.

SLAS discovery : advancing life sciences R & D
The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potent...

Improving domain generalization performance for medical image segmentation via random feature augmentation.

Methods (San Diego, Calif.)
Deep convolutional neural networks (DCNNs) have shown remarkable performance in medical image segmentation tasks. However, medical images frequently exhibit distribution discrepancies due to variations in scanner vendors, operators, and image quality...

Few-Shot Pixel-Precise Document Layout Segmentation via Dynamic Instance Generation and Local Thresholding.

International journal of neural systems
Over the years, the humanities community has increasingly requested the creation of artificial intelligence frameworks to help the study of cultural heritage. Document Layout segmentation, which aims at identifying the different structural components...

CaMeL-Net: Centroid-aware metric learning for efficient multi-class cancer classification in pathology images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cancer grading in pathology image analysis is a major task due to its importance in patient care, treatment, and management. The recent developments in artificial neural networks for computational pathology have demonstrated...

Visual-quality-driven unsupervised image dehazing.

Neural networks : the official journal of the International Neural Network Society
Most of the existing learning-based dehazing methods require a diverse and large collection of paired hazy/clean images, which is intractable to obtain. Therefore, existing dehazing methods resort to training on synthetic images. This may result in a...

DLATA: Deep Learning-Assisted transformation alignment of 2D brain slice histology.

Neuroscience letters
Accurate alignment of brain slices is crucial for the classification of neuron populations by brain region, and for quantitative analysis in in vitro brain studies. Current semi-automated alignment workflows require labor intensive labeling of featur...

Image Quality Improvement in Deep Learning Image Reconstruction of Head Computed Tomography Examination.

Tomography (Ann Arbor, Mich.)
In this study, we assess image quality in computed tomography scans reconstructed via DLIR (Deep Learning Image Reconstruction) and compare it with iterative reconstruction ASIR-V (Adaptive Statistical Iterative Reconstruction) in CT (computed tomogr...

A two-step deep learning method for 3DCT-2DUS kidney registration during breathing.

Scientific reports
This work proposed KidneyRegNet, a novel deep registration pipeline for 3D CT and 2D U/S kidney scans of free breathing, which comprises a feature network, and a 3D-2D CNN-based registration network. The feature network has handcrafted texture featur...