AIMC Topic: Unsupervised Machine Learning

Clear Filters Showing 181 to 190 of 797 articles

Adaptive Knowledge Distillation for High-Quality Unsupervised MRI Reconstruction With Model-Driven Priors.

IEEE journal of biomedical and health informatics Jun 6, 2024
Magnetic Resonance Imaging (MRI) reconstruction has made significant progress with the introduction of Deep Learning (DL) technology combined with Compressed Sensing (CS). However, most existing methods require large fully sampled training datasets t...
Humans Deep Learning Image Processing, Computer-Assisted Algorithms Brain Magnetic Resonance Imaging Unsupervised Machine Learning
View on PubMed DOI

Cycle contrastive adversarial learning with structural consistency for unsupervised high-quality image deraining transformer.

Neural networks : the official journal of the International Neural Network Society Jun 4, 2024
In overcoming the challenges faced in adapting to paired real-world data, recent unsupervised single image deraining (SID) methods have proven capable of accomplishing notably acceptable deraining performance. However, the previous methods usually fa...
Unsupervised Machine Learning Semantics Algorithms Image Processing, Computer-Assisted Humans Neural Networks, Computer
View on PubMed DOI

DREAMER: a computational framework to evaluate readiness of datasets for machine learning.

BMC medical informatics and decision making Jun 4, 2024
BACKGROUND: Machine learning (ML) has emerged as the predominant computational paradigm for analyzing large-scale datasets across diverse domains. The assessment of dataset quality stands as a pivotal precursor to the successful deployment of ML mode...
Datasets as Topic Unsupervised Machine Learning Supervised Machine Learning Humans Machine Learning Software Algorithms
View on PubMed DOI

Toward Ground-Truth Optical Coherence Tomography via Three-Dimensional Unsupervised Deep Learning Processing and Data.

IEEE transactions on medical imaging Jun 3, 2024
Optical coherence tomography (OCT) can perform non-invasive high-resolution three-dimensional (3D) imaging and has been widely used in biomedical fields, while it is inevitably affected by coherence speckle noise which degrades OCT imaging performanc...
Imaging, Three-Dimensional Humans Unsupervised Machine Learning Deep Learning Tomography, Optical Coherence
View on PubMed DOI

MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3-D CT Lesions.

IEEE transactions on neural networks and learning systems Jun 3, 2024
With the renaissance of deep learning, automatic diagnostic algorithms for computed tomography (CT) have achieved many successful applications. However, they heavily rely on lesion-level annotations, which are often scarce due to the high cost of col...
Databases, Factual Tomography, X-Ray Computed Neural Networks, Computer Algorithms Lung Neoplasms Unsupervised Machine Learning Deep Learning Imaging, Three-Dimensional Humans
View on PubMed DOI

Unsupervised domain adaptation with weak source domain labels via bidirectional subdomain alignment.

Neural networks : the official journal of the International Neural Network Society May 31, 2024
Unsupervised domain adaptation (UDA) enables knowledge transfer from a labeled source domain to an unlabeled target domain. However, UDA performance often relies heavily on the accuracy of source domain labels, which are frequently noisy or missing i...
Unsupervised Machine Learning Humans Algorithms Neural Networks, Computer Cluster Analysis
View on PubMed DOI

Expansive data, extensive model: Investigating discussion topics around LLM through unsupervised machine learning in academic papers and news.

PloS one May 31, 2024
This study presents a comprehensive exploration of topic modeling methods tailored for large language model (LLM) using data obtained from Web of Science and LexisNexis from June 1, 2020, to December 31, 2023. The data collection process involved que...
Language Humans Unsupervised Machine Learning
View on PubMed DOI

Enhancement of OCTimages by unsupervised deep learning.

Physics in medicine and biology May 30, 2024
. The quality of optical coherence tomography (OCT)images is crucial for clinical visualization of early disease. As a three dimensional and coherent imaging, defocus and speckle noise are inevitable, which seriously affect evaluation of microstructu...
Tomography, Optical Coherence Face Image Processing, Computer-Assisted Humans Unsupervised Machine Learning Deep Learning
View on PubMed DOI

Enhancing voxel-based dosimetry accuracy with an unsupervised deep learning approach for hybrid medical image registration.

Medical physics May 21, 2024
BACKGROUND: Deformable registration is required to generate a time-integrated activity (TIA) map which is essential for voxel-based dosimetry. The conventional iterative registration algorithm using anatomical images (e.g., computed tomography (CT)) ...
Image Processing, Computer-Assisted Unsupervised Machine Learning Radiometry Single Photon Emission Computed Tomography Computed Tomography Humans Deep Learning
View on PubMed DOI

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.

Radiation oncology (London, England) May 21, 2024
PURPOSE: Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net ba...
Unsupervised Machine Learning Brain Neoplasms Radiation Oncology Glioma Deep Learning Imaging, Three-Dimensional Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging
View on PubMed DOI
Popular Topics
Recent Journals