Zahra Mirikharaji,Kumar Abhishek,Alceu Bissoto et al.
Zahra Mirikharaji et al.
Skin cancer is a major public health problem that could benefit from computer-aided diagnosis to reduce the burden of this common disease. Skin lesion segmentation from images is an important step toward achieving this goal. However, the pr...
Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge [0.03%]
颅骨植入物设计的临床应用和计算效率研究：AutoImplant 2021颅骨植入物设计挑战赛综述
Jianning Li,David G Ellis,Oldřich Kodym et al.
Jianning Li et al.
Cranial implants are commonly used for surgical repair of craniectomy-induced skull defects. These implants are usually generated offline and may require days to weeks to be available. An automated implant design process combined with onsit...
Attentive continuous generative self-training for unsupervised domain adaptive medical image translation [0.03%]
自监督医学图像转换的注意力增强连续生成式自我训练方法
Xiaofeng Liu,Jerry L Prince,Fangxu Xing et al.
Xiaofeng Liu et al.
Self-training is an important class of unsupervised domain adaptation (UDA) approaches that are used to mitigate the problem of domain shift, when applying knowledge learned from a labeled source domain to unlabeled and heterogeneous target...
Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images [0.03%]
一种改进心脏MR图像分类深度学习模型校准的不确定性感知训练方法
Tareen Dawood,Chen Chen,Baldeep S Sidhu et al.
Tareen Dawood et al.
Quantifying uncertainty of predictions has been identified as one way to develop more trustworthy artificial intelligence (AI) models beyond conventional reporting of performance metrics. When considering their role in a clinical decision s...
Fahad Shamshad,Salman Khan,Syed Waqas Zamir et al.
Fahad Shamshad et al.
Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results and prompting researchers to reconsider the supremacy of conv...
Learning-based needle tip tracking in 2D ultrasound by fusing visual tracking and motion prediction [0.03%]
基于学习的二维超声针尖跟踪：视觉跟踪和运动预测融合方法
Wanquan Yan,Qingpeng Ding,Jianghua Chen et al.
Wanquan Yan et al.
Visual trackers are the most commonly adopted approach for needle tip tracking in ultrasound (US)-based procedures. However, they often perform unsatisfactorily in biological tissues due to the significant background noise and anatomical oc...
HAL-IA: A Hybrid Active Learning framework using Interactive Annotation for medical image segmentation [0.03%]
HAL-IA：一种使用交互式标注的医学图像分割混合主动学习框架
Xiaokang Li,Menghua Xia,Jing Jiao et al.
Xiaokang Li et al.
High performance of deep learning models on medical image segmentation greatly relies on large amount of pixel-wise annotated data, yet annotations are costly to collect. How to obtain high accuracy segmentation labels of medical images wit...
Amirhossein Kazerouni,Ehsan Khodapanah Aghdam,Moein Heidari et al.
Amirhossein Kazerouni et al.
Denoising diffusion models, a class of generative models, have garnered immense interest lately in various deep-learning problems. A diffusion probabilistic model defines a forward diffusion stage where the input data is gradually perturbed...
Body composition assessment with limited field-of-view computed tomography: A semantic image extension perspective [0.03%]
有限视野CT体组成评估：一种语义图像扩展视角
Kaiwen Xu,Thomas Li,Mirza S Khan et al.
Kaiwen Xu et al.
Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT-based body composition (BC) assessment as key anatomical structures are missing...
Sanat Ramesh,Vinkle Srivastav,Deepak Alapatt et al.
Sanat Ramesh et al.
The field of surgical computer vision has undergone considerable breakthroughs in recent years with the rising popularity of deep neural network-based methods. However, standard fully-supervised approaches for training such models require v...