MDPNet: a dual-path parallel fusion network for multi-modal MRI glioma genotyping [0.03%]
基于双轨并行融合网络的多模态磁共振胶质瘤分型方法(MDPNet)
Huaizhi Wang,Haichao Liu,Fang Du et al.
Huaizhi Wang et al.
Method: In this study, we propose a dual-path parallel fusion network (MDPNet) designed to comprehensively extract heterogeneous features across different MRI modalities while simultaneously predicting the molecular status of IDH, 1p/19q, and ATRX....Conclusion: The proposed framework exhibits significant advantages in integrating heterogeneous features from multi-modal MRI data.
A Novel Dynamic Neural Network for Heterogeneity-Aware Structural Brain Network Exploration and Alzheimer's Disease Diagnosis [0.03%]
一种用于异构性感知结构脑网络探索和阿尔茨海默病诊断的新型动态神经网络
Wenju Cui,Yilin Leng,Yunsong Peng et al.
Wenju Cui et al.
Specifically, we develop a 3-D dynamic convmixer to extract abundant heterogeneous features from sMRI first. Subsequently, the critical brain atrophy regions are identified by dynamic prototype learning with embedding the hierarchical brain semantic structure.
Insights into the mechanisms involved in the evolution of the structural and physicochemical properties of tomato during air drying - A study combining MRI, unilateral NMR and conventional techniques [0.03%]
结合MRI、单侧NMR和传统技术研究番茄干燥过程中结构及理化性质演变机制
Maja Musse,Amidou Traore,Alexandre Leca et al.
Maja Musse et al.
MRI and unilateral NMR succeeded in capturing tissue evolution and heterogeneous features of tomato slices during drying by accessing information on water status and distribution and apparent micro-porosity.
Developing multifunctional zwitterionic-xanthan gum-anchored network copolymers for biomedical applications [0.03%]
用于生物医学应用的多功能两性离子-黄原胶共聚物网络锚定系杂化材料的开发
Vikrant Sharma,Disha Kapil,Baljit Singh
Vikrant Sharma
FESEM and AFM analyses of these hydrogels demonstrated morphological heterogeneous features with surface roughness.
Multiple instance learning-based prediction of programmed death-ligand 1 (PD-L1) expression from hematoxylin and eosin (H&E)-stained histopathological images in breast cancer [0.03%]
基于多重实例学习的预测乳腺癌组织病理学图像中PD-L1表达水平的方法研究
Zhen Da,Heng Yang,Bianba Zhaxi et al.
Zhen Da et al.
These findings demonstrates that the Transformer-based TransMIL model can effectively capture highly heterogeneous features within the MIL framework, exhibiting strong cross-center generalization capabilities.
MIT-SAM: Medical Image-Text SAM with Mutually Enhanced Heterogeneous Features Fusion for Medical Image Segmentation [0.03%]
MIT-SAM：具有互惠增强的异构特征融合的医学图像文本SAM用于医学图像分割
Xichuan Zhou,Lingfeng Yan,Rui Ding et al.
Xichuan Zhou et al.
The ITIF block facilitates the mutual enhancement of homogeneous information among heterogeneous features and the SSTR method empowers the model to capture crucial details concerning lesion text, including location, quantity, and other key aspects.
A Microfluidic Approach for Quantitative Study of Spatial Heterogeneity in Bacterial Biofilms [0.03%]
定量研究细菌生物膜空间异质性的微流控方法
Yuzhen Zhang,Yumin Cai,Lingbin Zeng et al.
Yuzhen Zhang et al.
Through a special design of microfluidic chamber and spatially controllable bacteria seeding, biofilms are cultivated with customized semi-2D structure, which enables quantitative measurements of spatially heterogeneous features with time-lapse microscopy.
The Interplay Between Cervicovaginal Microbiota Diversity, Lactobacillus Profiles and Human Papillomavirus in Cervical Cancer: A Systematic Review [0.03%]
宫颈癌中宫颈阴道微生物群多样性，乳酸菌谱和人乳头瘤病毒之间的相互作用：系统性综述
Giosuè Giordano Incognito,Carlo Ronsini,Vittorio Palmara et al.
Giosuè Giordano Incognito et al.
A total of 22 studies (78.6%) assessed α-diversity, and 17 studies (60.7%) examined β-diversity; Conclusions: This study emphasizes the heterogeneous features of the studies exploring the association between alterations in the CVM, HPV, and the development of ICC, suggesting the need for further research
Multimodal medical image fusion combining saliency perception and generative adversarial network [0.03%]
结合显著性感知和生成对抗网络的多模态医学图像融合方法
Mohammed Albekairi,Mohamed Vall O Mohamed,Khaled Kaaniche et al.
Mohammed Albekairi et al.
Current fusion techniques face challenges in effectively combining heterogeneous features while preserving critical diagnostic information....This approach enables precise temporal Decomposition of heterogeneous features and robust quality assessment of fused regions. Experimental validation on diverse medical image datasets, encompassing multiple modalities and image dimensions, demonstrates the TDN's superior performance.
The spatiotemporal evolution of dissolved-phase NAPL plumes revealed by the integrated groundwater quality and machine learning models [0.03%]
综合地下水质量和机器学习模型揭示的溶解相NAPL羽状体的时空演化
Fei Qiao,Jinguo Wang,Jian Song et al.
Fei Qiao et al.
Additionally, the heterogeneous features and complex biogeochemical reactions in aquifers often limit the application of traditional numerical modeling.
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