PRIME: Phase reversed interleaved multi-Echo acquisition enables highly accelerated distortion-corrected diffusion MRI [0.03%]
基于相位反转的交错多回波采集技术实现高加速畸变校正扩散加权MRI
Yohan Jun,Qiang Liu,Ting Gong et al.
Yohan Jun et al.
High-resolution diffusion MRI (dMRI) is often constrained by the fundamental trade-off between geometric distortion, signal-to-noise ratio (SNR), and scan efficiency. The purpose of this study is to develop and evaluate a new pulse sequence...
Prediction of post-stroke brain swelling using biomechanical modelling and deep neural networks [0.03%]
基于生物力学建模和深度神经网络的急性脑卒中后脑水肿预测研究
Xi Chen,Wahbi El-Bouri,Stephen Payne et al.
Xi Chen et al.
Malignant stroke is a life-threatening condition, with mortality rates reaching up to 80% among patients managed conservatively. Brain swelling volume and midline shift are pivotal clinical markers for predicting stroke outcomes. However, b...
OOD-SEG: Exploiting out-of-distribution detection techniques for learning image segmentation from sparse multi-class positive-only annotations [0.03%]
利用出分布检测技术进行稀疏多类正样本标注图像分割学习
Junwen Wang,Zhonghao Wang,Oscar MacCormac et al.
Junwen Wang et al.
Despite significant advancements, segmentation based on deep neural networks in medical and surgical imaging faces several challenges, two of which we aim to address in this work. First, acquiring complete pixel-level segmentation labels fo...
NeuroGT: Biophysically grounded graph transformers for self-supervised representation learning of neuronal morphology [0.03%]
神经科学中的自监督表示学习：基于生物物理图形变换器的神经元形态表征学习（NeuroGT）
Pengpeng Sheng,Tingting Han,Gangming Zhao et al.
Pengpeng Sheng et al.
The intricate shape of a neuron is a fundamental determinant of its computational role, and its quantitative analysis is crucial for deciphering brain function. The advent of high-throughput imaging has produced neuronal reconstructions at ...
Harmonization in magnetic resonance imaging: A survey of acquisition, image-level, and feature-level methods [0.03%]
磁共振影像的调和化：采集、图像和特征层面的方法综述
Qinqin Yang,Firoozeh Shomal-Zadeh,Ali Gholipour
Qinqin Yang
Magnetic resonance imaging (MRI) has greatly advanced neuroscience research and clinical diagnostics. However, imaging data collected across different scanners, acquisition protocols, or imaging sites often exhibit substantial heterogeneity...
Predicting neoadjuvant therapy response in breast cancer from preoperative biopsy via spatial-semantic-differential learning and interpretable clinicopathological-guided fusion [0.03%]
基于空间语义差分学习和可解释临床病理指导融合的乳腺癌新辅助治疗反应预测模型
Wen-Tai Hou,Zi-Fei Pu,Ze-Yan Xu et al.
Wen-Tai Hou et al.
Predicting pathological complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer remains challenging due to high tumor heterogeneity and disparities across data modalities. This study introduces a multimodal learning framework ...
Ultrasound Localization Microscopy Learned from power doppler by uncertainty frequency density estimation and semantic consistency awareness [0.03%]
基于不确定性频率密度估计和语义一致性感知的学习功率多普勒的超声定位显微镜技术
Qinghua Lin,Xuan Ren,Boqian Zhou et al.
Qinghua Lin et al.
Ultrasound Localization Microscopy (ULM) achieves micron-level vascular visualization beyond the resolution of conventional ultrasound imaging by tracking microbubble positions. However, ULM relies on high-frame-count ultrasound images, whi...
Functional imaging constrained diffusion for brain PET synthesis from structural MRI [0.03%]
基于结构MRI的脑PET图像合成的约束扩散方法研究
Minhui Yu,Mengqi Wu,Ling Yue et al.
Minhui Yu et al.
Magnetic resonance imaging (MRI) and positron emission tomography (PET) are increasingly used in multimodal analysis of neurodegenerative disorders. While MRI is broadly utilized in clinical settings, PET is less accessible. Many studies ha...
GCN combined with snake convolution for enhanced topological perception in thrombotic hepatic portal vein segmentation [0.03%]
结合蛇形卷积的GCN在血栓性门静脉分割中的拓扑感知增强作用研究
Lijuan Ma,Weiguang Wang,Xingshun Qi et al.
Lijuan Ma et al.
The hemodynamic status of the portal vein plays a crucial role in the identification, treatment, and prognostic prediction of complications associated with liver cirrhosis. Accurate segmentation of the portal vein is essential for quantitat...
Dose-aware diffusion model for 3D PET image denoising: Multi-institutional validation with reader study and real low-dose data [0.03%]
基于剂量的3D PET图像降噪扩散模型：多机构验证、读者研究和真实低剂量数据评估
Huidong Xie,Weijie Gan,Reimund Bayerlein et al.
Huidong Xie et al.
Reducing scan times, radiation dose, and enhancing image quality, especially for lower-performance scanners, are critical in low-count/low-dose PET imaging. Deep learning (DL) techniques have been investigated for PET image denoising. Howev...