Due to the exorbitant expense of obtaining labeled data in the field of medical image analysis, semi-supervised learning has emerged as a favorable method for the segmentation of anatomical structures. Although semi-supervised learning techniques hav...
Neural networks : the official journal of the International Neural Network Society
Oct 31, 2024
Graph Contrastive Learning (GCL) has recently emerged as a promising graph self-supervised learning framework for learning discriminative node representations without labels. The widely adopted objective function of GCL benefits from two key properti...
Medical & biological engineering & computing
Oct 30, 2024
Deep neural networks have reached remarkable achievements in medical image processing tasks, specifically in classifying and detecting various diseases. However, when confronted with limited data, these networks face a critical vulnerability, often s...
Deep learning-based automated segmentation of vascular structures in preoperative CT angiography (CTA) images contributes to computer-assisted diagnosis and interventions. While CTA is the common standard, non-contrast CT imaging has the advantage of...
Monitoring and predicting the environmental impact of wastewater is essential for sustainable aquaculture. The environmental DNA metabarcoding-integrated supervised machine learning (SML) algorithm is an alternative method for ecological quality asse...
BACKGROUND: In response to the inadequacy of manual analysis in meeting the rising demand for retinal optical coherence tomography (OCT) images, a self-supervised learning-based clustering model was implemented.
BACKGROUND: Effective molecular feature representation is crucial for drug property prediction. Recent years have seen increased attention on graph neural networks (GNNs) that are pre-trained using self-supervised learning techniques, aiming to overc...
Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strategy in 2035. A descriptive, retrospective review of medical records of patients, who were diagnosed wi...
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Oct 23, 2024
An integral stage in typical digital pathology workflows involves deriving specific features from tiles extracted from a tessellated whole-slide image. Notably, various computer vision neural network architectures, particularly the ImageNet pretraine...
Neural networks : the official journal of the International Neural Network Society
Oct 22, 2024
Sparsely annotated image segmentation has attracted increasing attention due to its low labeling cost. However, existing weakly-supervised shadow detection methods require complex training procedures, and there is still a significant performance gap ...