TempoSafe-CVS: A Temporal Multi-scale Deep Learning Framework for Automated Assessment of the Critical View of Safety in Laparoscopic Cholecystectomy [0.03%]
一种自动评估腹腔镜胆囊切除术安全关键视图的时空多尺度深度学习框架
Hafsa Gulzar,Deboch Eyob Abera,Muhammad Zubair Nawaz et al.
Hafsa Gulzar et al.
Accurate assessment of the critical view of safety (CVS) is essential for preventing bile duct injuries during laparoscopic cholecystectomy. Existing artificial intelligence approaches primarily rely on static frame-level analysis and often...
Fully Automated Segmentation of Anatomical Subregions of the Thoracolumbar Spine on Computed Tomography [0.03%]
全自动 CT 扫描腰椎解剖亚区域分割
Raffaele Da Mutten,Sven Theiler,Massimo Bottini et al.
Raffaele Da Mutten et al.
Segmentations of the vertebral column that include anatomical subregions can be used for patient education, pedicle screw planning, or radiomic feature extraction for spinal surgery. Deep learning has proven successful in tackling medical i...
CONRep: Uncertainty-Aware Vision-Language Report Drafting Using Conformal Prediction [0.03%]
基于协形预测的不确定性感知视觉语言报告起草模型 CONRep
Danial Elyassirad,Benyamin Gheiji,Mahsa Vatanparast et al.
Danial Elyassirad et al.
The objective of this study is to quantify uncertainty in vision-language model (VLM)-based automated radiology report drafting (ARRD) to support trustworthy clinical deployment. In this study, we developed CONRep in two settings: label-bas...
Sex-Related Performance Disparities in Convolutional Neural Networks for Imaging-Based Assessment of Coronary Atherosclerosis and Ischemic Heart Disease: A Systematic Review [0.03%]
基于影像的冠状动脉动脉粥样硬化和缺血性心脏病评估中卷积神经网络性别差异的系统评价
Aya Mudrik,Ayala Dodge,Alon Moore Galindo et al.
Aya Mudrik et al.
Sex-related disparities persist in the diagnosis and management of ischemic heart disease (IHD), raising concern that convolutional neural networks (CNNs) used in coronary imaging may perpetuate these inequities. This systematic review eval...
Sex-Related Performance Disparities in Convolutional Neural Networks for Imaging-Based Assessment of Coronary Atherosclerosis and Ischemic Heart Disease: A Systematic Review [0.03%]
基于影像的冠状动脉动脉粥样硬化和缺血性心脏病评估中卷积神经网络的性别差异性能：一项系统综述
Aya Mudrik,Ayala Dodge,Alon Moore Galindo et al.
Aya Mudrik et al.
Sex-related disparities persist in the diagnosis and management of ischemic heart disease (IHD), raising concern that convolutional neural networks (CNNs) used in coronary imaging may perpetuate these inequities. This systematic review eval...
Learning Geometric Information Propagation for Semi-supervised 3D Medical Image Segmentation [0.03%]
几何信息传播学习在半监督的医学图像三维分割中的应用
Lianyuan Yu,Xiuzhen Guo,Ji Shi et al.
Lianyuan Yu et al.
Semi-supervised learning enhances medical image segmentation by leveraging unlabeled data, reducing reliance on extensive labeled datasets. We observe that medical images usually exhibit consistent anatomical structures defined by geometric...
Rethinking Architectural Complexity in Deep Vision Models for Histopathological Image Classification [0.03%]
深度视觉模型在组织病理图像分类中的架构复杂性再思考
Qaiser Abbas,Muhammad Irzam Liaqat,Sabahat Qayum et al.
Qaiser Abbas et al.
Recent advances in deep learning for histopathological image analysis have led to increasingly complex architectures that require substantial computational resources and large datasets. While these models achieve strong performance, they of...
LDM-Echo: A Latent Diffusion Model for Echocardiographic Image Denoising with Clinical Evaluation [0.03%]
基于临床评估的心脏超声图像去噪的潜在扩散模型(LDM-Echo)
Samira Jaballah,Tarak Ben Said,Imen Baklouti et al.
Samira Jaballah et al.
Speckle noise in echocardiographic imaging degrades contrast, obscures anatomical structures, and compromises quantitative measurements. Effective suppression of this noise is critical, yet traditional denoising methods often cause structur...
pix2pixHDv2: Efficient Panoramic Dental Image Synthesis with Minimal Artifacts and Computational Overhead [0.03%]
带极少伪影和计算开销的高效全景牙科图像合成Pix2PixHDv2
Merter Hami Karacan,Sait Can Yucebas
Merter Hami Karacan
Although recent image-generation studies have achieved promising results, they still present challenges in terms of computational cost and training/inference time that need to be addressed. Conditional generative adversarial networks (mask-...
Bidirectional Weighted Cross-Entropy for Imbalanced Pressure Injury Classification [0.03%]
不平衡压力性损伤的双向加权交叉熵分类方法
Jong Chan Yeom,Eun Jin Han,Ah Young Kim et al.
Jong Chan Yeom et al.
Accurate classification of pressure injuries from clinical images remains challenging because clinical datasets are often small and class-imbalanced. We propose bidirectional weighted cross-entropy (BWCE), a conditional prediction-dependent...