CATERPillar: a flexible framework for generating white matter numerical substrates with incorporated glial cells [0.03%]
caterpillar：一种生成包含胶质细胞的白质数值底物的灵活框架
Jasmine Nguyen-Duc,Malte Brammerloh,Melina Cherchali et al.
Jasmine Nguyen-Duc et al.
Monte Carlo diffusion simulations in numerical substrates are valuable for exploring the sensitivity and specificity of the diffusion MRI (dMRI) signal to realistic cell microstructure features. A crucial component of such simulations is th...
Transfer learning from 2D natural images to 4D fMRI brain images via geometric mapping [0.03%]
基于几何映射的迁移学习：从2D自然图象到4D脑fMRI图像
Kai Gao,Lubin Wang,Liang Li et al.
Kai Gao et al.
Functional magnetic resonance imaging (fMRI) allows real-time observation of brain activity through blood oxygen level-dependent (BOLD) signals and is extensively used in studies related to sex classification, age estimation, behavioral mea...
UNISELF: A unified network with instance normalization and self-ensembled lesion fusion for multiple sclerosis lesion segmentation [0.03%]
基于实例归一化和自集成病灶融合的多发性硬化症病灶分割统一网络
Jinwei Zhang,Lianrui Zuo,Blake E Dewey et al.
Jinwei Zhang et al.
Automated segmentation of multiple sclerosis (MS) lesions using multicontrast magnetic resonance (MR) images improves efficiency and reproducibility compared to manual delineation, with deep learning (DL) methods achieving state-of-the-art ...
C2HFusion: Clinical context-driven hierarchical fusion of multimodal data for personalized and quantitative prognostic assessment in pancreatic cancer [0.03%]
基于临床背景的多模态数据层次化融合实现胰腺癌个性化预后量化评估(C2HFusion)
Bolun Zeng,Yaolin Xu,Peng Wang et al.
Bolun Zeng et al.
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Accurate prognostic modeling enables reliable risk stratification to identify patients most likely to benefit from adjuvant therapy, thereby facilitating individuali...
Advances in automated fetal brain MRI segmentation and biometry: Insights from the FeTA 2024 challenge [0.03%]
2024年FeTA挑战赛中的胎儿大脑MRI自动分割和生物测量的进展及洞察
Vladyslav Zalevskyi,Thomas Sanchez,Misha Kaandorp et al.
Vladyslav Zalevskyi et al.
Accurate fetal brain tissue segmentation and biometric measurement are essential for monitoring neurodevelopment and detecting abnormalities in utero. The Fetal Tissue Annotation (FeTA) Challenges have established robust multi-center benchm...
Quasi-multimodal-based pathophysiological feature learning for retinal disease diagnosis [0.03%]
基于准多模态的视网膜疾病病理生理特征学习方法
Lu Zhang,Huizhen Yu,Zuowei Wang et al.
Lu Zhang et al.
Retinal diseases spanning a broad spectrum can be effectively identified and diagnosed using complementary signals from multimodal data. However, multimodal diagnosis in ophthalmic practice is typically challenged in terms of data heterogen...
AEM: An interpretable multi-task multi-modal framework for cardiac disease prediction [0.03%]
可解释的多任务心脏疾病预测模型 AEM框架
Jiachuan Peng,Marcel Beetz,Abhirup Banerjee et al.
Jiachuan Peng et al.
Cardiovascular disease (CVD) is one of the leading causes of death and illness across the world. Especially, early prediction of heart failure (HF) is complicated due to the heterogeneity of its clinical presentations and symptoms. These ch...
Rethinking fairness in medical imaging: Maximizing group-specific performance with application to skin disease diagnosis [0.03%]
重新思考医学影像中的公平性：最大化特定群体的性能在皮肤疾病诊断中的应用
Gelei Xu,Yuying Duan,Jun Xia et al.
Gelei Xu et al.
Recent efforts in medical image computing have focused on improving fairness by balancing it with accuracy within a single, unified model. However, this often creates a trade-off: gains for underrepresented groups can come at the expense of...
Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge [0.03%]
2024年PhaKIR挑战赛中的内窥镜手术阶段识别、仪器关键点估计和仪器实例分割的比较验证结果
Tobias Rueckert,David Rauber,Raphaela Maerkl et al.
Tobias Rueckert et al.
Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, ...
Predicting diabetic macular edema treatment responses using OCT: Dataset and methods of APTOS competition [0.03%]
用于预测糖尿病黄斑水肿治疗反应的OCT数据集和方法(APTOS竞赛)
Weiyi Zhang,Peranut Chotcomwongse,Yinwen Li et al.
Weiyi Zhang et al.
Diabetic macular edema (DME) significantly contributes to visual impairment in diabetic patients. Treatment responses to intravitreal therapies vary, highlighting the need for patient stratification to predict therapeutic benefits and enabl...