Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge
The emergence of deep learning has considerably advanced the state-of-the-art in cardiac
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …
magnetic resonance (CMR) segmentation. Many techniques have been proposed over the …
Autoencoder based self-supervised test-time adaptation for medical image analysis
Deep neural networks have been successfully applied to medical image analysis tasks like
segmentation and synthesis. However, even if a network is trained on a large dataset from …
segmentation and synthesis. However, even if a network is trained on a large dataset from …
[图书][B] Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1 …
The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908
constitutes the refereed proceedings of the 24th International Conference on Medical Image …
constitutes the refereed proceedings of the 24th International Conference on Medical Image …
Multi-task learning for thyroid nodule segmentation with thyroid region prior
Thyroid nodule segmentation in ultrasound images is a valuable and challenging task, and it
is of great significance for the diagnosis of thyroid cancer. Due to the lack of the prior …
is of great significance for the diagnosis of thyroid cancer. Due to the lack of the prior …
A super-resolution guided network for improving automated thyroid nodule segmentation
Background and Objective: A thyroid nodule is an abnormal lump that grows in the thyroid
gland, which is the early symptom of thyroid cancer. In order to diagnose and treat thyroid …
gland, which is the early symptom of thyroid cancer. In order to diagnose and treat thyroid …
Joint spine segmentation and noise removal from ultrasound volume projection images with selective feature sharing
Volume Projection Imaging from ultrasound data is a promising technique to visualize spine
features and diagnose Adolescent Idiopathic Scoliosis. In this paper, we present a novel …
features and diagnose Adolescent Idiopathic Scoliosis. In this paper, we present a novel …
Wave-san: Wavelet based style augmentation network for cross-domain few-shot learning
Previous few-shot learning (FSL) works mostly are limited to natural images of general
concepts and categories. These works assume very high visual similarity between the …
concepts and categories. These works assume very high visual similarity between the …
The segmentation effect of style transfer on fetal head ultrasound image: a study of multi-source data
M Zhou, C Wang, Y Lu, R Qiu, R Zeng, D Zhi… - Medical & biological …, 2023 - Springer
The generalization ability of the fetal head segmentation method is reduced due to the data
obtained by different machines, settings, and operations. To keep the generalization ability …
obtained by different machines, settings, and operations. To keep the generalization ability …
Style curriculum learning for robust medical image segmentation
The performance of deep segmentation models often degrades due to distribution shifts in
image intensities between the training and test data sets. This is particularly pronounced in …
image intensities between the training and test data sets. This is particularly pronounced in …
Training deep learning models to work on multiple devices by cross-domain learning with no additional annotations
Purpose To create an unsupervised cross-domain segmentation algorithm for segmenting
intraretinal fluid and retinal layers on normal and pathologic macular OCT images from …
intraretinal fluid and retinal layers on normal and pathologic macular OCT images from …