Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis [0.03%]
基于多尺度表示注意的深度多重实例学习在全片数字病理图像分析中的应用
Hangchen Xiang,Junyi Shen,Qingguo Yan et al.
Hangchen Xiang et al.
Recently, convolutional neural networks (CNNs) directly using whole slide images (WSIs) for tumor diagnosis and analysis have attracted considerable attention, because they only utilize the slide-level label for model training without any a...
Hypergraph-regularized multimodal learning by graph diffusion for imaging genetics based Alzheimer's Disease diagnosis [0.03%]
基于影像遗传学的阿尔茨海默病诊断的超图正则化多模态学习方法
Meiling Wang,Wei Shao,Shuo Huang et al.
Meiling Wang et al.
Recent studies show that multi-modal data fusion techniques combining information from diverse sources are helpful to diagnose and predict complex brain disorders. However, most existing diagnosis methods have only simply employed a feature...
Discriminative ensemble meta-learning with co-regularization for rare fundus diseases diagnosis [0.03%]
基于协同正则化的判别式元学习集成方法用于罕见眼底疾病诊断
Mengdi Gao,Hongyang Jiang,Lei Zhu et al.
Mengdi Gao et al.
Deep neural networks (DNNs) have been widely applied in the medical image community, contributing to automatic ophthalmic screening systems for some common diseases. However, the incidence of fundus diseases patterns exhibits a typical long...
Dive into the details of self-supervised learning for medical image analysis [0.03%]
深入探讨医学图像分析的自监督学习细节
Chuyan Zhang,Hao Zheng,Yun Gu
Chuyan Zhang
Self-supervised learning (SSL) has achieved remarkable performance in various medical imaging tasks by dint of priors from massive unlabeled data. However, regarding a specific downstream task, there is still a lack of an instruction book o...
Anatomy-guided domain adaptation for 3D in-bed human pose estimation [0.03%]
基于解剖学的领域自适应三维卧姿人体姿态估计方法
Alexander Bigalke,Lasse Hansen,Jasper Diesel et al.
Alexander Bigalke et al.
3D human pose estimation is a key component of clinical monitoring systems. The clinical applicability of deep pose estimation models, however, is limited by their poor generalization under domain shifts along with their need for sufficient...
CholecTriplet2022: Show me a tool and tell me the triplet - An endoscopic vision challenge for surgical action triplet detection [0.03%]
基于内窥镜视觉的手术操作三元组检测挑战赛：展示器械并判断其三元组-CholecTriplet2022
Chinedu Innocent Nwoye,Tong Yu,Saurav Sharma et al.
Chinedu Innocent Nwoye et al.
Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. The benefit is that this formalization helps to obtain a more ...
Multi-target landmark detection with incomplete images via reinforcement learning and shape prior embedding [0.03%]
基于强化学习和形状先验的多目标地标检测（不完整图像）
Kaiwen Wan,Lei Li,Dengqiang Jia et al.
Kaiwen Wan et al.
Medical images are generally acquired with limited field-of-view (FOV), which could lead to incomplete regions of interest (ROI), and thus impose a great challenge on medical image analysis. This is particularly evident for the learning-bas...
Stephan Dooper,Hans Pinckaers,Witali Aswolinskiy et al.
Stephan Dooper et al.
Current hardware limitations make it impossible to train convolutional neural networks on gigapixel image inputs directly. Recent developments in weakly supervised learning, such as attention-gated multiple instance learning, have shown pro...
High-resolution feature based central venous catheter tip detection network in X-ray images [0.03%]
基于高分辨率特征的中央静脉导管尖端检测网络在X射线图像中的应用
Yuhan Wang,Hak Keung Lam,Zeng-Guang Hou et al.
Yuhan Wang et al.
Hospital patients can have catheters and lines inserted during the course of their admission to give medicines for the treatment of medical issues, especially the central venous catheter (CVC). However, malposition of CVC will lead to many ...
Gradient modulated contrastive distillation of low-rank multi-modal knowledge for disease diagnosis [0.03%]
用于疾病诊断的低秩多模知识的梯度调制对比蒸馏
Xiaohan Xing,Zhen Chen,Yuenan Hou et al.
Xiaohan Xing et al.
The fusion of multi-modal data, e.g., medical images and genomic profiles, can provide complementary information and further benefit disease diagnosis. However, multi-modal disease diagnosis confronts two challenges: (1) how to produce disc...