AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 311 to 320 of 9890 articles

Lesion boundary detection for skin lesion segmentation based on boundary sensing and CNN-transformer fusion networks.

Artificial intelligence in medicine
Traditional convolutional neural networks often struggle to capture global information and handle ambiguous boundaries during complex skin lesion segmentation tasks. To tackle this challenge, we proposed MPBA-Net, a hybrid network that integrates mul...

Predicting clinical outcomes using 18F-FDG PET/CT-based radiomic features and machine learning algorithms in patients with esophageal cancer.

Nuclear medicine communications
OBJECTIVE: This study evaluated the relationship between 18F-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) radiomic features and clinical parameters, including tumor localization, histopathological subtype, lymph node metastasis, mortal...

UltraBones100k: A reliable automated labeling method and large-scale dataset for ultrasound-based bone surface extraction.

Computers in biology and medicine
BACKGROUND: Ultrasound-based bone surface segmentation is crucial in computer-assisted orthopedic surgery. However, ultrasound images have limitations, including a low signal-to-noise ratio, acoustic shadowing, and speckle noise, which make interpret...

Vascular segmentation of functional ultrasound images using deep learning.

Computers in biology and medicine
Segmentation of medical images is a fundamental task with numerous applications. While MRI, CT, and PET modalities have significantly benefited from deep learning segmentation techniques, more recent modalities, like functional ultrasound (fUS), have...

Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.

Proceedings of the National Academy of Sciences of the United States of America
Characterizing the conformational ensemble of biomolecular systems is key to understand their functions. Cryoelectron microscopy (cryo-EM) captures two-dimensional snapshots of biomolecular ensembles, giving in principle access to thermodynamics. How...

Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.

Science advances
Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color consistency in computer vision, color constancy in human perception, and color accuracy in biomedical ...

Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms.

Scientific reports
Prenatal healthcare development requires accurate automated techniques for fetal ultrasound image segmentation. This approach allows standardized evaluation of fetal development by minimizing time-exhaustive processes that perform poorly due to human...

Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications.

Scientific reports
Recent research advances have resulted in an experimental benchtop X-ray fluorescence computed tomography (XFCT) system that likely meets the imaging dose/scan time constraints for benchtop XFCT imaging of live mice injected with gold nanoparticles (...

Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision.

Scientific reports
Craniofacial morphometrics in sharks provide crucial insights into evolutionary history, geographical variation, sexual dimorphism, and developmental patterns. However, the fragile cartilaginous nature of shark craniofacial skeleton poses significant...

Application of ConvNeXt with transfer learning and data augmentation for malaria parasite detection in resource-limited settings using microscopic images.

PloS one
Malaria continues to be a severe health problem across the globe, especially within resource-limited areas which lack both skilled diagnostic personnel and diagnostic equipment. This study investigates the use of deep learning diagnosis for malaria t...