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Weakly supervised machine learning
Supervised learning aims to build a function or model that seeks as many map**s as
possible between the training data and outputs, where each training data will predict as a …
possible between the training data and outputs, where each training data will predict as a …
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond
Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …
registration over the past decade. The initial developments, such as regression-based and U …
Transmorph: Transformer for unsupervised medical image registration
In the last decade, convolutional neural networks (ConvNets) have been a major focus of
research in medical image analysis. However, the performances of ConvNets may be limited …
research in medical image analysis. However, the performances of ConvNets may be limited …
Correlation-aware coarse-to-fine mlps for deformable medical image registration
Deformable image registration is a fundamental step for medical image analysis. Recently
transformers have been used for registration and outperformed Convolutional Neural …
transformers have been used for registration and outperformed Convolutional Neural …
Modality-agnostic structural image representation learning for deformable multi-modality medical image registration
Establishing dense anatomical correspondence across distinct imaging modalities is a
foundational yet challenging procedure for numerous medical image analysis studies and …
foundational yet challenging procedure for numerous medical image analysis studies and …
Deep learning-based lung image registration: A review
H ** to solve series problems in clinical applications. Since the lungs are soft and fairly …
SAM: Self-supervised learning of pixel-wise anatomical embeddings in radiological images
Radiological images such as computed tomography (CT) and X-rays render anatomy with
intrinsic structures. Being able to reliably locate the same anatomical structure across …
intrinsic structures. Being able to reliably locate the same anatomical structure across …
Data-efficient unsupervised interpolation without any intermediate frame for 4d medical images
Abstract 4D medical images which represent 3D images with temporal information are
crucial in clinical practice for capturing dynamic changes and monitoring long-term disease …
crucial in clinical practice for capturing dynamic changes and monitoring long-term disease …
Deep Learning in Medical Image Registration: Magic or Mirage?
Classical optimization and learning-based methods are the two reigning paradigms in
deformable image registration. While optimization-based methods boast generalizability …
deformable image registration. While optimization-based methods boast generalizability …
Mutual information guided diffusion for zero-shot cross-modality medical image translation
Cross-modality data translation has attracted great interest in medical image computing.
Deep generative models show performance improvement in addressing related challenges …
Deep generative models show performance improvement in addressing related challenges …