Toward robust histopathology imaging: An unsupervised framework for artifact detection, localization, and restoration [0.03%]
一种鲁棒病理学成像方法：无监督框架在缺陷检测、定位和修复中的应用
Huaishui Yang,Mengye Lyu,Huhan Xie et al.
Huaishui Yang et al.
Whole Slide Images are central to modern pathology and computational histopathology. However, tissue processing and slide scanning can introduce artifacts that degrade image quality and hinder computer-aided diagnosis (CAD) systems. Therefo...
MINeR: Direction-modulated implicit neural representation enables ultrafast multi-shell diffusion MRI [0.03%]
MINR：方向调节的隐式神经表示可实现超快多壳扩散MRI
Tian Zeng,Jie Feng,Tong Sun et al.
Tian Zeng et al.
Diffusion magnetic resonance imaging (dMRI) enables noninvasive mapping of tissue microstructure by probing water molecule diffusivity. While advanced multi-shell diffusion models offer improved sensitivity to cellular properties, their req...
Progressive growing of patch size: Curriculum learning for accelerated and improved medical image segmentation [0.03%]
逐块增长的医学图像分割加速与改进方法
Stefan M Fischer,Johannes Kiechle,Laura Daza et al.
Stefan M Fischer et al.
In this work, we introduce Progressive Growing of Patch Size (PGPS), an automatic curriculum learning approach for 3D medical image segmentation. Curriculum learning structures the training process by presenting progressively more complex s...
Adapting pathology foundation models for continual cross-center WSI retrieval [0.03%]
适应病理基础模型以实现持续的跨中心WSI检索
Xinyu Zhu,Zhiguo Jiang,Kun Wu et al.
Xinyu Zhu et al.
The construction of medical centers is rapidly advancing, generating a vast amount of whole slide images (WSIs). Content-based histopathological image retrieval (CBHIR) unlocks the rich digital morphologic content of WSIs previously confine...
PathFound: An agentic multimodal model activating evidence-seeking pathological diagnosis [0.03%]
PathFound：一种代理式多模态模型激活的证据寻租式病理诊断模型
Shengyi Hua,Jianfeng Wu,Tianle Shen et al.
Shengyi Hua et al.
Recent pathological foundation models have substantially advanced visual representation learning and multimodal interaction. However, most models still rely on a static inference paradigm. They only analyze whole-slide images once to produc...
Motion-compensated implicit neural modeling for 3D multiparametric quantitative MRI [0.03%]
基于运动补偿的隐式神经建模的三维定量磁共振成像参数映射技术
Guoyan Lao,Xiaopeng Zong,Chen Liu et al.
Guoyan Lao et al.
Multiparametric quantitative MRI (MP-qMRI) provides comprehensive 3D tissue characterization in neuroimaging but remains highly susceptible to involuntary head motion. Motion correction in 3D MP-qMRI is particularly challenging, as even sub...
Contrastive Discrepancy: A label-free metric for deformable image registration supporting testing-time hyperparameter selection [0.03%]
对比差异性：无标签度量，支持测试时超参数选择的可变形图像配准
Xia Li,Jihe Li,Weijie Wang et al.
Xia Li et al.
Deformable image registration (DIR) proves critical to many medical image analysis tasks, yet its reliable evaluation is fundamentally challenged by the absence of ground-truth deformations. Existing label-based metrics require costly manua...
SPADE: Spatial transcriptomics and pathology alignment using a mixture of data experts for an expressive latent space [0.03%]
基于数据专家混合的SPADE方法学习具有表达式的潜在空间来进行空间转录组与病理图像对齐
Ekaterina Redekop,Mara Pleasure,Zichen Wang et al.
Ekaterina Redekop et al.
The rapid growth of digital pathology and advances in self-supervised deep learning have enabled the development of foundational models for various pathology tasks across diverse diseases. While multimodal approaches integrating diverse dat...
Causality-Guided Diffusion and Fusion of incomplete multi-modal data for robust survival prognosis [0.03%]
基于因果引导的不完整多模态数据扩散与融合的鲁棒生存预测
Yuying Huang,Xiaorou Zheng,Shoubin Dong
Yuying Huang
Accurate integration of whole-slide images (WSIs) and genomic data is essential for improving the reliability and interpretability of survival prognosis. However, current methods face core challenges of insufficient robustness in both cross...
OmniPathoVQA: Benchmarking pathology vision-language models with Encyclopedia-scale knowledge [0.03%]
OmniPathoVQA：使用百科全书规模知识基准病理学视觉语言模型
Kaitao Chen,Linda Wei,Shaohao Rui et al.
Kaitao Chen et al.
Pathology vision-language models (VLMs) are promising for building the clinical decision support systems. However, a key barrier to real-world clinical deployment lies in the lack of rigorous and clinically meaningful model evaluation. Exis...