Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI [0.03%]
基于合成的成像-分化表示学习在多序列3D/4D磁共振成像中的应用
Luyi Han,Tao Tan,Tianyu Zhang et al.
Luyi Han et al.
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences. However, redundant information exists across sequences, which interferes with mining efficient represent...
Riemannian frameworks for the harmonization of resting-state functional MRI scans [0.03%]
调制静息态功能MRI扫描的黎曼结构框架
Nicolas Honnorat,Sudha Seshadri,Ron Killiany et al.
Nicolas Honnorat et al.
Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols can significantly impact MRI scans. The development of statistical methods able to reduce this variability without alte...
FiCRoN, a deep learning-based algorithm for the automatic determination of intracellular parasite burden from fluorescence microscopy images [0.03%]
基于深度学习的荧光显微图像细胞内寄生虫负荷自动测定算法FiCRoN
Graciela Juez-Castillo,Brayan Valencia-Vidal,Lina M Orrego et al.
Graciela Juez-Castillo et al.
Protozoan parasites are responsible for dramatic, neglected diseases. The automatic determination of intracellular parasite burden from fluorescence microscopy images is a challenging problem. Recent advances in deep learning are transformi...
Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image [0.03%]
基于局部病理图像预测基因表达的准确可解释视觉骨干网络：带有卷积和图节点联合嵌入的变压器模型
Xiao Xiao,Yan Kong,Ronghan Li et al.
Xiao Xiao et al.
Inferring gene expressions from histopathological images has long been a fascinating yet challenging task, primarily due to the substantial disparities between the two modality. Existing strategies using local or global features of histolog...
Simón Oxenford,Ana Sofía Ríos,Barbara Hollunder et al.
Simón Oxenford et al.
Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & mo...
Residual Aligner-based Network (RAN): Motion-separable structure for coarse-to-fine discontinuous deformable registration [0.03%]
基于残差对齐网络（RAN）的粗到精非连续变形配准的运动分离结构
Jian-Qing Zheng,Ziyang Wang,Baoru Huang et al.
Jian-Qing Zheng et al.
Deformable image registration, the estimation of the spatial transformation between different images, is an important task in medical imaging. Deep learning techniques have been shown to perform 3D image registration efficiently. However, c...
Interpretable and intervenable ultrasonography-based machine learning models for pediatric appendicitis [0.03%]
基于超声影像的可解释和可干预的机器学习模型在儿童急性阑尾炎中的应用研究
Ričards Marcinkevičs,Patricia Reis Wolfertstetter,Ugne Klimiene et al.
Ričards Marcinkevičs et al.
Appendicitis is among the most frequent reasons for pediatric abdominal surgeries. Previous decision support systems for appendicitis have focused on clinical, laboratory, scoring, and computed tomography data and have ignored abdominal ult...
An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training [0.03%]
一种高效的半监督质量控制系统，使用基于物理的MRI伪影生成器和对抗训练进行训练
Daniele Ravi;Alzheimer’s Disease Neuroimaging Initiative;Frederik Barkhof,Daniel C Alexander,Lemuel Puglisi et al.
Daniele Ravi;Alzheimer’s Disease Neuroimaging Initiative;Frederik Barkhof et al.
Large medical imaging data sets are becoming increasingly available. A common challenge in these data sets is to ensure that each sample meets minimum quality requirements devoid of significant artefacts. Despite a wide range of existing au...
Joint learning framework of cross-modal synthesis and diagnosis for Alzheimer's disease by mining underlying shared modality information [0.03%]
通过挖掘潜在的共享模式信息联合学习阿尔茨海默病跨模态合成和诊断的框架
Chenhui Wang,Sirong Piao,Zhizhong Huang et al.
Chenhui Wang et al.
Alzheimer's disease (AD) is one of the most common neurodegenerative disorders presenting irreversible progression of cognitive impairment. How to identify AD as early as possible is critical for intervention with potential preventive measu...
Combiner and HyperCombiner networks: Rules to combine multimodality MR images for prostate cancer localisation [0.03%]
组合器和超组合器网络：用于前列腺癌定位的多模态MR图像组合规则
Wen Yan,Bernard Chiu,Ziyi Shen et al.
Wen Yan et al.
One of the distinct characteristics of radiologists reading multiparametric prostate MR scans, using reporting systems like PI-RADS v2.1, is to score individual types of MR modalities, including T2-weighted, diffusion-weighted, and dynamic ...