Towards a universal JPEG lossless recompression foundation model for pathology images: A transformer context modeling approach [0.03%]
面向病理图像的通用JPEG无损再压缩基础模型：一种变压器上下文建模方法
Tao Song,Rong Tao,Chunyan Wu et al.
Tao Song et al.
Lossless recompression of JPEG images remains fundamentally constrained by the limited modeling capacity of traditional context-mixing entropy estimators, yielding suboptimal compression ratios. Recently, CNN-based learned recompression met...
ViGNet: A clinical data-supported deep learning approach for NSCLC immunotherapy response prediction in digital pathology [0.03%]
基于临床数据的深度学习方法用于预测数字病理学中非小细胞肺癌免疫治疗反应(ViGNet)
Luoyi Kong,Shaowei Wu,Canjia Cai et al.
Luoyi Kong et al.
Histopathology is the cornerstone of oncology diagnosis, while whole-slide images (WSIs) enable the transition to digital, quantitative pathology. Leveraging WSIs to accurately predict therapeutic response is increasingly vital for advancin...
Beyond attention heatmaps: How to get better explanations for multiple instance learning models in histopathology [0.03%]
超越注意力热图：如何获得更好的解释以改进组实例学习模型在组织病理学中的应用
Mina Jamshidi Idaji,Julius Hense,Tom Neuhäuser et al.
Mina Jamshidi Idaji et al.
Multiple instance learning (MIL) has enabled substantial progress in computational histopathology, where a large amount of patches from gigapixel whole slide images are aggregated into slide-level predictions. Heatmaps are widely used to va...
Diffusion-based cross-staining feature transformation for whole slide image analysis: From H&E to IHC representation learning [0.03%]
基于扩散的跨染色特征转换用于全片扫描图像分析：从H&E到IHC表示学习
Jialong Zhong,Miao Zhang,Leiye Liu et al.
Jialong Zhong et al.
In computational pathology, Hematoxylin and Eosin (H&E) staining offers a cost-effective solution for tissue analysis, while Immunohistochemistry (IHC) delivers specific biomarker expression at substantially higher cost and operational comp...
From pixels to polygons: A survey of deep learning approaches for medical image-to-mesh reconstruction [0.03%]
从像素到多边形：医学图像到网格重建的深度学习方法综述
Fengming Lin,Arezoo Zakeri,Yidan Xue et al.
Fengming Lin et al.
Deep learning-based medical image-to-mesh reconstruction has rapidly evolved, enabling the transformation of medical imaging data into three-dimensional mesh models that are critical in computational medicine and in silico trials for advanc...
AWPAUNet: An advanced surrogate for real-time simultaneous modeling of multiple mechanical fields of soft tissues [0.03%]
AWPAUNet：一种先进的代理模型，用于软组织多个力学场的实时同步建模
Ziyang Hu,Shenghui Liao,Rui Luo et al.
Ziyang Hu et al.
Real-time mechanical modeling of soft tissues using deep learning has long been a research hotspot in surgical simulation. Current studies predominantly focus on scenarios where soft tissues are subjected to external concentrated forces, wh...
KGT: Knowledge-guided graph transformer for neurodegenerative disease diagnosis and brain age prediction with MRI [0.03%]
基于知识引导的图变换器在神经退行性疾病诊断和脑部年龄预测中的应用MRI
Jingyu Zhao,Rizhi Ding,Manhua Liu
Jingyu Zhao
Deep learning methods have significantly advanced the analysis of brain imaging data for various downstream tasks such as disease diagnosis and age prediction. However, most existing methods train deep models on large amounts of imaging dat...
CardioMorphNet: Cardiac motion prediction using a shape-guided Bayesian recurrent deep network [0.03%]
基于形状引导的贝叶斯循环深度网络的心脏运动预测方法
Reza Akbari Movahed,Abuzar Rezaee,Arezoo Zakeri et al.
Reza Akbari Movahed et al.
Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnormalities. Existing methods often struggle to accurately capture heart motion because they re...
3D craniofacial generative model for surgical planning in mandibular reconstruction [0.03%]
下颌骨重建手术规划的三维颅面生成模型
Chenfan Xu,Zhentao Liu,Jiamin Wu et al.
Chenfan Xu et al.
Mandibular reconstruction following segmental resection for oral tumors is a complex procedure necessitating precise restoration of both masticatory function and facial aesthetics. Current Computer-Assisted Surgery (CAS) workflows remain fr...
Mohammad Reza Hosseinzadeh Taher,Michael B Gotway,Jianming Liang
Mohammad Reza Hosseinzadeh Taher
Humans effortlessly interpret images by parsing them into part-whole hierarchies. Yet, deep learning models, despite excelling at capturing multi-level features, often fail to explicitly encode these part-whole hierarchies-an essential aspe...